Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection

Mohammed A. Al-Ghamdi; Khalid S. Al-Gahtani

doi:10.3390/su14042126

Al-Ghamdi, Mohammed A.;Al-Gahtani, Khalid S.

2022-02-13 00:00:00

sustainability Article Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection Mohammed A. Al-Ghamdi and Khalid S. Al-Gahtani * Civil Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia; [email protected] * Correspondence: [email protected] Abstract: Selecting a suitable heating, ventilation, and air-conditioning (HVAC) system is critical, because it impacts a building’s life cycle cost (LCC). Several factors affect the selection decision, such as quality, buildability, internal and external building appearance, HVAC size and weight, and LCC. These criteria are difﬁcult to measure, as they are not based on agreed measurement units. Another challenging factor in the selection process is assessing the building’s function/performance and determining its HVAC needs. Currently, the decision depends mostly on expert knowledge, and there is no agreed-upon systematic method to follow. This paper aims to develop a systematic model for selecting HVAC systems based on the value engineering (VE) concept. The model identiﬁed fourteen criteria based on an agreed standard test for objective criteria and a typical evaluation for subjective criteria. These HVAC criteria were assessed using a combination of the AHP, pairwise, function analysis system (FAST), and Monte Carlo techniques. As a result, a complete model was developed to enhance the selection process, programmed within the building information modeling (BIM) environment platform. Several HVAC experts were interviewed and more than twenty expert opinions were collected to validate the model. In addition, a case study building in Riyadh, Saudi Arabia, was implemented using the programmed HVAC selection model for validation purposes. The programmed model can signiﬁcantly facilitate the selection process for designers. Citation: Al-Ghamdi, M.A.; Keywords: value engineering; quality; AHP; FAST; BIM; Monte Carlo; HVAC system; life cycle cost Al-Gahtani, K.S. Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection. Sustainability 2022, 14, 2126. https://doi.org/10.3390/su14042126 1. Introduction The critical procurement process for heating, ventilation, air-conditioning, and re- Academic Editor: Jaejun Kim frigerant (HVAC&R) systems can irritate decision-makers, as buildings contribute about Received: 6 January 2022 40% of global energy consumption [1]. Most energy used in buildings is for HVAC, Accepted: 11 February 2022 which consumes about 50% of building energy on average [2]. The industry for HVAC so- Published: 13 February 2022 lutions in Saudi Arabia is expected to reach a value up to USD 6.36 billion by 2022. The total HVAC market in Saudi Arabia represents close to 2% of the global HVAC market [3]. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in Thus, selecting high-efﬁciency HVAC systems in construction is crucial to building published maps and institutional afﬁl- sustainable buildings [4]. The role of HVAC systems in the engineering process has iations. already been well recognized. One of the vital tasks in designing a building is selecting an appropriate HVAC system. Satisfying the end speciﬁcations of a company requires deﬁning an HVAC system with different functionalities. There is an extensive array of HVAC systems, with various properties to meet different design requirements. The availability Copyright: © 2022 by the authors. of many different HVAC systems combined with the complicated relationships between Licensee MDPI, Basel, Switzerland. selection criteria makes the selection process difﬁcult and time-consuming. A systematic This article is an open access article and efﬁcient approach to assessing HVAC systems is necessary in order to select the best distributed under the terms and alternative for a given building. conditions of the Creative Commons To analyze these criteria, value engineering (VE) is utilized in this study to select Attribution (CC BY) license (https:// the best HVAC system when designing a building. It provides maximum value when creativecommons.org/licenses/by/ the function continuously performs using the best option. A core VE concept is to select 4.0/). Sustainability 2022, 14, 2126. https://doi.org/10.3390/su14042126 https://www.mdpi.com/journal/sustainability Sustainability 2022, 14, 2126 2 of 30 any design option or material with the maximum value index in order to determine the material quality and to consider building function over life cycle cost (LCC). This relation is formulated in Equation (1) [5]: Value = (Function + Quality)/Cost (1) The types and classiﬁcations of HVAC systems vary; therefore, the selection process is essential to boost performance and reduce costs. The quality criteria need to be deﬁned and weighted for measurement along with cost. Moreover, measuring quality criteria is affected by the building functions (needs and performance) in addition to considering maximum quality at the lowest possible cost; this is the standard deﬁnition of VE. This study explored the deﬁnitions and components of current HVAC systems used in Saudi Arabia by using local and international standards. In addition, the study used previous research to reach accurate quality criteria that ﬁt with the HVAC function. The function analysis system technique (FAST) and interviews with HVAC experts were used to estimate the weight of each criterion. The study established a model for forecasting the LCC of the HVAC system to be used. Finally, for the method to be used efﬁciently by practitioners, the overall system was programmed using an application programming interface (API) for building information modeling (BIM) in order to include the process in BIM tools. A case study of one King Saud University endowment building in Riyadh, Saudi Arabia, was selected in this study to verify the proposed model. Five HVAC system alternatives were considered in this case study: water chiller, air chiller, variable refrigerant ﬂow (VRF), rooftop packaged, and split wall mounted. The results based on the case study showed the highest score for the VRF system. The degree of accuracy of the study outputs was measured by experts and compared with an actual building operation and management contract. Additional veriﬁcation was carried out through two questionnaires, one explaining the entire study mechanism and one explaining the results of applying this method to the case study. The responses to the questionnaires indicated a high degree of approval. The contributions of the study to the body of knowledge are as follows: deﬁnitions of fourteen agreed-upon criteria based on the Saudi market, measured based on a standard test and quantitative subjective scale; weighting of criteria ranking and importance, based on consultations with several specialist experts, for ofﬁce buildings (one of thirteen identiﬁed building types); development of a forecast HVAC and LCC model using Monte Carlo techniques; and development of an automated model to integrate the proposed model with BIM. This automated HVAC selection model can assist designers and building owners in making informed decisions when selecting the best choice among various HVAC options. 2. Literature Review There are many studies in the area of HVAC energy and process selection because of its impact on building occupancy and energy consumption. List of studies in each study area are provided in the following subsections. 2.1. HVAC System Evaluation Process and Methods Multiple criteria decision-making (MCDM) was the primary method used when reviewing previous studies. There are several methods for obtaining the criteria weights of an MCDM problem, one of which is the entropy method. Milani et al. [6] used the entropy method to assess the weights of criteria in MCDM. Table 1 describes the evaluation processes in a selection of previous studies that, from the authors’ perspective, are important and relevant to the present work. 2.2. HVAC System Evaluation Criteria As reported in previous research, the selection of an HVAC system usually depends on energy consumption, thermal comfort, and air quality [13]. The inﬂuence of the HVAC Sustainability 2022, 14, 2126 3 of 30 system is vital, because it can contribute to reducing the energy consumption of a building and preserving appropriate indoor air quality [14]. In addition, the important criteria of choosing an HVAC system have to be considered, such as a low noise level in the building [15]. Furthermore, the ASHRAE standards give importance to the criterion of durability. Shahrestani et al. [16] summarized the evaluation methods used in the selection process in 15 references from 1989 to 2016, including quantitative and qualitative methods. In a more recent study, Baç et al. [17] reviewed 23 studies of selection methods using one or more MCDM techniques. In addition, they integrated the hybrid application of building energy simulation (BES), modiﬁed stepwise weight assessment ratio analysis (SWARA), and weighted additive sum product assessment (WASPAS) to asset the HVAC decision making process. BIM was used to provide building geometries, HVAC system layouts, and spatial information as inputs to compute potential energy implications if occupancy diversity is eliminated [18]. Other studies focused on the many objectives that serve HVAC evaluation. Table 2 lists these papers and describes their importance in the HVAC ﬁeld. Table 1. Studies on evaluating material selection process. Reference Technique Importance Output of each criterion inﬂuences Butler et al. [7] Criteria weights overall performance relative to other criteria Analytical hierarchy Karayalcin [8] Calculating criteria weight in MCDM process (AHP) AHP breaks down MCDM problem into Saaty et al. [9] AHP hierarchical system Decision model uses a series Shahinur et al. [10] Manage collection of competing criteria of possible objective functions Shift focus of building design solution from performance to impact Provide broader building Integrated building impact Hu [11] assessment framework that includes assessment framework energy, water, environment, health Demonstrate feasibility of proposed integrated assessment framework Framework for material selection with Decision support system (DSS) Nwodo et al. [12] integration of cost, energy, carbon, and in BIM mechanical strength Table 2. Studies on inﬂuence of HVAC aspects. Reference Objective Importance Calculation of building Use of different weather, climate, and Labus [19] cooling demand layout and design Considers national Australian built Al-Waked et al. [20] Energy simulation model environment rating system rules for collecting and using data Use of sensor-based building management system, outside air Che [13] A way to save building energy dehumidiﬁcation, and two-stage particle ﬁlter system Emphasis on importance of ventilation Guo et al. [21]. Review of HVAC guidelines to eliminate airborne transmission risk Sustainability 2022, 14, 2126 4 of 30 2.3. Value Engineering (VE) VE is simply a methodology in the construction sector that assures the best desirable quality with less-expensive options [5]. It is an effective strategy for enhancing building quality while keeping costs low and quality high. VE is more than a cost-cutting strategy; it adds value to services by altering and improving functionalities. The true goal of VE, however, is to improve value, which is deﬁned as the ratio of function to cost. Thus, value can be increased by either increasing the function or lowering the cost [22]. Table 3 summarizes previous studies on material selection applying the VE concept. Table 3. Studies on material selection by applying VE. Reference Objective Technique Marzouk [23] Support for decision-makers VE ELECTRE III model Performance of building Lee [24] VE numerical model components and LCC analysis Importance of evolving Mao et al. [25] construction project Traditional VE management techniques Green building design VE and neuro-linguistic Wao [26] and construction programming (NLP) Link between cost and energy VE and BIM Wei and Chen [27] savings in architectural design simulation technologies Probability technique with AHP Labuan and Waty [28] Evaluation of ﬂooring materials and FAST Indexing model using vector Lee [29] Evaluation of ﬂooring materials normalization method Selection of ﬂooring Alrahhal Alorabi et al. [30] VE concept ﬁnishing materials 2.4. Analytical Hierarchy Process (AHP) The AHP was proposed by Saaty [31] to solve hierarchical problems by minimizing complex decisions, turning them into a series of pairwise comparisons and then producing the outcomes. As a result, the AHP aids in identifying both subjective and objective aspects of a decision. It includes an effective technique for validating the consistency of evaluations by decision-makers. As a result, any potential bias in the decision-making process will be reduced. Because the scores, and eventually the ﬁnal ranking, can be obtained by relative pairwise evaluations of both the criteria and the options provided by the user, AHP has become a remarkably ﬂexible and efﬁcient tool [32]. The pairwise comparison approach has several advantages, including that it requires only two criteria to be thoroughly reviewed simultaneously [33]. The AHP can be completed in three simple steps: (1) Create a vector of criteria weights (2) Calculate the score matrix (3) Arrange the possibilities in order of preference 2.5. HVAC System Alternatives HVAC is the technology of indoor and vehicular environmental comfort. The purpose is to provide thermal comfort and adequate indoor air quality. HVAC is an essential part of residential structures such as single-family homes, apartment buildings, hotels, senior living facilities, and medium to large industrial and ofﬁce buildings. It has been classiﬁed according to the energy efﬁciency of small air-conditioners (single- package window type and single split-system ducted and non-ducted air-conditioners using air-cooled condensers, with capacity not exceeding 65,000 Btu/h [34]) and the en- ergy efﬁciency of large air-conditioners (electrically operated air-conditioners, condensing Sustainability 2022, 14, 2126 5 of 30 units, chillers, absorption chillers, electrically operated variable refrigerant ﬂow (VRF) air-conditioners, close control air-conditioners, and condensing units serving computer rooms [35]). 2.6. Deﬁning Total HVAC System Selection Criteria: Quality, Buildability, Sustainability, and Durability Some academics have described quality in terms of providing customer service or products without defects [36]. Brieﬁng documents must identify the HVAC system spec- iﬁcations. In general, different quality parameters can be established, prioritized, and accurately calculated, and the weighting of criteria can help in evaluating selected options. HVAC system evaluations are carried out by quality tests and measurements by speciﬁc standards. According to previous studies, there are six criteria for quality, as described in Table 4. Table 4. Summary of quality criteria. Criterion Description References Efﬁciency of HVAC SASO 2663, 2874 [34,35], C1: Energy efﬁciency ratio electricity consumption Almutairi et al. [37] Amount of air volume needed ASHRAE standard 62, C2: Air volume of system in place 55 [38,39] C3: Centralized place for Air diffuser position to Crown Power [40] air diffuser distribute air C4: Heating conditioning Heating options based on Carrier [41] in system heat pumps C5: Sound rating level System noise Farhad et al. [15] Use of fresh air in C6: Air replenishment ASHRAE standard 62.1 [42] HVAC system In addition to criteria related to evaluating HVAC quality, according to previous studies, other criteria in the HVAC selection process are related to aesthetics, buildability, sustainability, and durability [16,17]. Eight HVAC selection criteria associated with system quality are described in Table 5. 2.7. Deﬁning the HVAC System’s LCC LCC is the sum of all costs incurred during the AC’s lifespan. This includes the unit’s purchasing and operating costs, such as energy expenditure, repair, and maintenance. The relation for cumulative cost is formulated as in Equation (2): LCC = IC + OC (2) The operating cost is deﬁned by Equation (3) [52]: OC = EC + MC (3) where LCC is life cycle cost, IC is initial cost, OC is operating cost, EC is energy cost, and MC is maintenance or service cost for maintaining equipment operation. Operating cost and its categories are described in Table 6. Several papers applied cost analysis using the Hourly Analysis Program (HAP) to calculate operating costs. 2.8. Applying Monte Carlo Simulation Tool Construction projects typically involve large sums of money. One of the most chal- lenging tasks in the construction business is determining and quantifying risks and their inﬂuence on project costs. Peleskei et al. [56] investigated how Monte Carlo simulation could be used to estimate the cost of a construction project. They looked at whether the Sustainability 2022, 14, 2126 6 of 30 various cost aspects in a building project would follow a particular probability distribution. The inﬂuence of correlations between different project expenses on the Monte Carlo sim- ulation outcome was investigated in this study. According to the ﬁndings, Monte Carlo simulation could be a valuable tool for risk managers and can be used to estimate building project costs. According to the research, cost distributions are favorably skewed, and cost factors appear to have some interdependent links. Table 5. Summary of aesthetic, buildability, sustainability, and durability criteria. Criteria Description References Appearance of HVAC system C7: Aesthetic system and overlap with Bakhter [43] building design Dimensions of HVAC system Jiayou and Yanxin [44] C8: Dimensions of HVAC units occupying spaces Camejo and Hittle [45] Effects of HVAC units on Jiayou and Yanxin [44] C9: Weights of HVAC units the building Camejo and Hittle [45] C10: Ease of HVAC installation Simple installation and Adams [46] or construction construction of HVAC system Hon [47] Fire alarm system is a C11: Linking of HVAC system low-current application; its Wayne et al. [48] with ﬁre alarm system function is to control spread of smoke from ﬁre source Environmental issues can affect Whole Building Design C12: System’s system: energy consumption, Guide [49] environmental efﬁciency CO and pollutant emissions, Balaras et al. [50] solid waste, water use Time under normal use ASHRAE HVAC conditions without unnecessary C13: Lifetime of HVAC system Applications Handbook, maintenance or 1999 [51] repair expenditure After-sale services (spare parts, ASHRAE HVAC C14: Agent’s ability to specialized labor) provided Applications provide services by seller Handbook [51] Table 6. Operating cost categories. Category Name Description Reference Results HAP used to measure cooling load and energy to Badran [53] Cost of electricity determine cost of energy in Energy cost (EC) consumption to cost analysis operate HVAC system HAP used to quickly Yasin [54] compare energy costs of HVAC system alternatives Maintenance cost measured Cost to keep system with values of variables such Maintenance cost under control and Verma et al. [55] as labor cost, downtime of (MC) prevent failure HVAC system, number of man-hours, and others Chang and El-Sheikh [57] performed a quantitative risk assessment of LCC risk man- agement for a project using the Monte Carlo simulation approach. Recently, Fan et al. [58] presented an enhanced cooling load prediction reliability method. The input parameters are calibrated ofﬂine via Monte Carlo simulations and stochastic treatment before being input into the prediction model. Sustainability 2022, 14, 2126 7 of 30 2.9. Linking the Evaluation Process with Building Information Modeling (BIM) Autodesk Revit, one of the well-known tools of BIM, represents a building as an interactive database using parametric building modeling technology [59]. Revit ensures that external functions can be added to the BIM model through what is known as an API. From the database, BIM has different dimensions (3D, 4D, 5D, . . . ND), and each dimension represents a speciﬁc type of data (cost, scheduling, sustainability, etc.) [60]. In the development of a new dimension of BIM related to VE, one of this paper ’s long-term objectives is to aid decision-makers in selecting optimal HVAC systems based on function, quality, and cost in a more automated manner and with a new VE BIM dimension. This analysis process can be related to the BIM model, obtaining values for alternative systems by specifying only the system type utilizing the API. Table 7 lists papers that mention the advantages of BIM regarding HVAC selection. Table 7. Papers mentioning advantages of BIM regarding HVAC selection. Reference Purpose Technique Assist HVAC analysis tools to Knight et al. [61] recognize room as separate zone BIM in the HVAC design for managing thermal comfort Knowledge repository in operating BIM systems in the Golabchi et al. [62] life to improve productivity and facility management reduce decision-making costs Enhance post-occupancy review Motawa and Carter [63] process while meeting industry Hypothetical BIM-based model sustainability requirements Investigate effects of different BIM platform + orthogonal Zhao et al. [64] envelope structural factors on simulation design cooling and heating loads Achieve ideal energy-efﬁcient Zahid et al. [65] DynamicPMV interior temperature 3. Research Methodology This research was aimed at selecting high-value HVAC systems. The proposed method- ology outlines the necessary steps in selecting an HVAC system. The criteria are assessed, the quality score measured, and the overall cost of the life cycle calculated. Finally, the appropriate system is chosen by assessing each system’s value, then linked to BIM in order to automate the output. Figure 1 describes the phases in this study. 3.1. Phase 1: Collect Data This phase included a comprehensive search of published papers, reports, catalogs, and standard manuals. In addition, several meetings were held with HVAC suppliers dur- ing exhibition events or while visiting local air-conditioning stores. This task was aimed at understanding the needs and gaps in the HVAC selection process. The outcome of this task was the development of a plan and methodology for implementing the introduced model. 3.2. Phase 2: Develop Selected HVAC Systems for Buildings Model Dominant criteria derived from previous literature reviews, international quality standards, and expert assessments were used in this study’s research technique. Several international quality standards were utilized to establish the required quality of HVAC systems, including ISO, SASO, and ASHREA. Many of these standards have been adapted to Saudi Arabia by the Saudi Standards Metrology and Quality Organization (SASO). Water chiller, air chiller, variable refrigerant ﬂow, packaged rooftop, and split wall mounted are examples of HVAC systems. This research was aimed at ﬁnding the Sustainability 2022, 14, 2126 8 of 30 most prevalent criteria and reducing them to a reasonable size. In the process, the authors communicated with specialists and quality engineers from several well-known companies. Furthermore, the method determines weights for prior criteria using decision-makers (design experts) as guides. The steps below describe the procedure for evaluating the HVAC systems model. The model was then linked to the BIM model to make data entry easier and to automate the output. After that, the case of an ofﬁce building was investi- Sustainability 2022, 14, 2126 8 of 32 gated, a report was written, and the research ﬁndings were conﬁrmed using the provided validation method. Figure 1. Flowchart of research methodology. Figure 1. Flowchart of research methodology. A research approach was planned to meet the research goal. Figure 2 illustrates the 3.1. Phase 1: Collect Data model for selecting HVAC systems. The entire methodology was applied to the case study This phase included a comprehensive search of published papers, reports, catalogs, and BIM integration. There are six steps in the procedure. The ﬁrst is to decide on the and st prand edominant ard manu criteria alwhile s. In keeping addition, the HV sev AC era system l meet ining mind. s were he The nextld w step is itto h HV calculate AC suppliers the criteria weight (CW) for each HVAC system criterion using functional analysis. The during exhibition events or while visiting local air-conditioning stores. This task was quality weight (QW) for each system is then determined using the AHP/pairwise/FAST aimed at understanding the needs and gaps in the HVAC selection process. The outcome techniques, based on the total criteria quality weight (CQW) evaluated using the accepted of this task was the development of a plan and methodology for implementing the intro- measurement unit and multiplied by CW. In addition, the LCC of systems is calculated duced mo based del. on a developed forecasting model utilizing the Monte Carlo technique. Finally, for each system alternative, the value score (V) is derived by dividing QW by LCC. Table 8 shows CW, CQW, QW, LCC, and V for examples of three HVAC alternatives and three 3.2. Phase 2: Develop Selected HVAC Systems for Buildings Model criteria in a tabulated form, as a way to simplify and better convey the links between these Dominant criteria derived from previous literature reviews, international quality variables according to the AHP method. standards, and expert assessments were used in this study’s research technique. Several international quality standards were utilized to establish the required quality of HVAC systems, including ISO, SASO, and ASHREA. Many of these standards have been adapted to Saudi Arabia by the Saudi Standards Metrology and Quality Organiza- tion (SASO). Water chiller, air chiller, variable refrigerant flow, packaged rooftop, and split wall mounted are examples of HVAC systems. This research was aimed at finding the most prevalent criteria and reducing them to a reasonable size. In the process, the authors communicated with specialists and quality engineers from several well-known companies. Furthermore, the method determines weights for prior criteria using decision-makers (design experts) as guides. The steps below describe the procedure for evaluating the HVAC systems model. The model was then linked to the BIM model to make data entry easier and to automate the output. After that, the case of an office building was investi- gated, a report was written, and the research findings were confirmed using the provided validation method. A research approach was planned to meet the research goal. Figure 2 illustrates the model for selecting HVAC systems. The entire methodology was applied to the case study and BIM integration. There are six steps in the procedure. The first is to decide on the predominant criteria while keeping the HVAC system in mind. The next step is to Sustainability 2022, 14, 2126 9 of 32 calculate the criteria weight (CW) for each HVAC system criterion using functional anal- ysis. The quality weight (QW) for each system is then determined using the AHP/pair- wise/FAST techniques, based on the total criteria quality weight (CQW) evaluated using the accepted measurement unit and multiplied by CW. In addition, the LCC of systems is calculated based on a developed forecasting model utilizing the Monte Carlo technique. Finally, for each system alternative, the value score (V) is derived by dividing QW by LCC. Table 8 shows CW, CQW, QW, LCC, and V for examples of three HVAC alternatives and Sustainability 2022, 14, 2126 9 of 30 three criteria in a tabulated form, as a way to simplify and better convey the links between these variables according to the AHP method. Figure 2. Flowchart of HVAC model selection process. Figure 2. Flowchart of HVAC model selection process. Sustainability 2022, 14, 2126 10 of 30 Table 8. Model of variables and calculations. HVAC Criteria Criteria Weight HVAC System 1 HVAC System 2 HVAC System 3 Criterion 1 CW1 CQW11 CQW12 CQW13 Criterion 2 CW2 CQW21 CQW22 CQW23 Criterion 3 CW3 CQW31 CQW32 CQW33 QW QW1 QW2 QW3 LCC LCC1 LCC2 LCC3 VS VS1 VS2 VS3 Finally, because the model follows a systematic method, the next stage connects the model to the BIM model in order to streamline data input and automate output. A general discussion to illustrate the model concept is presented in this section. Following that, a case study of an ofﬁce building is presented, along with detailed calculation information. The case study results are analyzed and summarized at the end. The rest of the section demonstrates these procedures and steps. 3.2.1. Step 1: Choose the Predominant Criteria The task of determining the evaluation criteria can be accomplished in various ways. Searching the literature and grouping all of the criteria into acceptable items is one way. Another approach is to research international HVAC system standards, which is usually followed by a standard test to determine the quality criteria. Typically, these standard tests recommend a minimum number of measured objects for the system to be accepted. These standards aim to preserve safety and health and measure, analyze, and manage quality and protect the environment [66]. Because of their high dependability and quantitative measuring, these standards are a good reference for completing this activity. Quality, buildability, sustainability, and durability are among the criteria used in the evaluation. To determine the most critical evaluation criteria, the following tasks are undertaken: Task 1: Identify the HVAC systems commonly used in the local market that are suitable for building functions and applications. Five HVAC systems were determined according to SASO 2663, 2874 with expert sessions based on the most typical projects used in Saudi Arabia, which are: 1. Chiller (water) 2. Chiller (air) 3. Variable refrigerant ﬂow (VRF) 4. Rooftop package 5. Wall-mounted split Task 2: Identify the building category and performance based on fourteen building types and structure classiﬁcations [67] as stated on Table 9: Table 9. Building types and classiﬁcations [67]. 1. Ofﬁce buildings 8. Gathering buildings 2. Residential buildings 9. Religious buildings 3. Retail buildings 10. Educational buildings 4. Hospitality buildings 11. Industrial buildings 5. Multi-purpose buildings (mall/ofﬁce space) 12. Agricultural buildings 6. Institutional civic buildings 13. Terminals (hospitals and clinics) (transportation buildings) 7. Institutional civic buildings 14. Recreational buildings (libraries and museums) (ﬁtness centers) Task 3: Collect technical speciﬁcations of HVAC systems from reputable suppliers and manufacturers and research those products on the appropriate websites, along with Sustainability 2022, 14, 2126 11 of 30 the standards and their reference. Table 10 shows identiﬁed criteria corresponding to the references. Table 10. Preliminary criteria obtained from literature review. Criteria References Coefﬁcient of performance, regulation performance, multi-purpose application, frosting, noise, life span, environmental Liu and Zhao [68] protection, ease of use, space occupied, ease of construction, maintenance Energy, user satisfaction, environment Avgelis and Papadopoulos [69] Energy efﬁciency ratio SASO 2663, 2874 [34,35] ASHRAE Standard 62-2001 [38] ASHRAE Standard 55-2004 [39] American Society of Heating, Air volume of system Refrigerating, and Air Conditioning Engineers [70] Supply air diffuser sizing and location, crown Centralized place for air diffuser power air-conditioning site [40] Carrier, residential products, heat pumps (heat Heating conditioning in system pumps vs. air-conditioners) [41] Sound rating level Farhad et al. [15] Air replenishment ASHRAE Standard 62.1 [42] Aesthetics of system Ihsan [43] Liu and Zhao [44] Camejo and Hittle [45] Measure dimensions, weights of HVAC units Wang et al. [71] Arroyo et al. [72] Adams [46] Measure ease of installation or construction Hon [47] Moore and Rietz [48] Link system with ﬁre alarm system WBDG Sustainable Committee [49] Evaluate system environmental efﬁciency Balaras et al. [50] Evaluate lifetime of system, agent’s ability to ASHRAE HVAC Applications Handbook 7 [51] provide services Based on the main questionnaire given to speciﬁc experts, fourteen criteria were identiﬁed, as shown in Tables 4 and 5. The authors considered all criteria in previous studies in the elimination process. Shahrestani et al. [16] reviewed overall papers from 1989–2017 to cover the criteria that could affect the HVAC selection process. In a recent study, Baç et al. [17] deﬁned six HVAC selection criteria and 27 subcriteria extracted from 72 references. These two related comprehensive studies are veriﬁed in this study. Task 4: Eliminate unrelated criteria to simplify the evaluation process. First, we extracted 32 criteria that affect the selection of HVAC systems. These were presented in the main questionnaire to specialists to determine the most common and inﬂuential criteria Sustainability 2022, 14, 2126 12 of 30 when selecting HVAC systems (refer to Phase 5). The results in Table 11 showed that the following criteria are the most common: Table 11. The most common criteria. 1. Energy efﬁciency ratio 8. Dimensions 2. Air volume 9. Weights 3. Centralized air outlet 10. Installation or construction 4. Heating option 11. Link to low-current application (ﬁre alarm) 5. Sound rating level 12. Environmental efﬁciency 6. Air replenishment 13. System lifetime 7. Aesthetics 14. Agent’s ability to provide services To recheck the criteria eliminated by the experts, the HVAC’s functions/sub-functions were used to compare the fourteen chosen criteria with the eliminated criteria. The com- parison was performed to ensure that the ﬁnal criteria would cover all functions. Table 12 shows the chosen criteria associated with the eliminated criteria and their functions. Table 12. Chosen criteria with preliminary equivalent criteria. Function Chosen Criteria Eliminated Criteria Energy use, efﬁciency, contribution to Energy efﬁciency ratio net-zero energy Air volume Thermal comfort Air outlet centralization - HVAC system quality Heating option - Sound rating level Low noise level CO emissions, indoor air quality, fresh Air replenishment air, concentration Ceiling space requirement, required space, Dimensions ﬂoor space encroachment, loss of usable ﬂoor space Weights - High HVAC system suitable System complexity, simplicity, and simple buildability implementation difﬁculties; future, current, Installation or construction layout, perimeter partition ﬂexibility; module integration Link to low-current application (ﬁre alarm) - Good appearance, Aesthetics Outdoor appearance, visual impact Environmental criterion, water consumption, good sustainability choice Environmental efﬁciency environmental protection System lifetime Lifetime, lead time, reliability, maturity Long durability Vendor viability and continued availability Agent’s ability to perform services of support Task 5: After identifying the fourteen HVAC selected criteria, objective and subjective criteria values needed to be measured. Evaluation methods were identiﬁed with numer- ical values to measure the objective and subjective criteria, as shown in Table 13. These measured criteria were identiﬁed based on prior research and experimentation standards. Then, they were presented to experts in the ﬁeld via interviews for validation. The experts conﬁrmed the optimal value of the quality criteria to be normalized as numbers later and simpler to read. These numbers are also presented in Table 13. Sustainability 2022, 14, 2126 13 of 30 Table 13. Evaluation methods and optimum values of CQW for fourteen predetermined HVAC system criteria. Highest HVAC No. Criterion Optimal Value Unit Evaluation Method System Value Energy efﬁciency ratio SASO 2663, 2874 [34,35], C1 36 Btu/h.w Water chiller max. = 36 (EER) Almutairi et al. [37] ASHRAE Standard 62, 55 Air handling unit C2 Air volume 87,581 CFM [38,39] max. = 87,581 Depending on air outlet Centralized place for Air outlet placed in center Available (= 1) location (wall or center of C3 Available (= 1) air outlet of room to cover more area or Not (= 0) room) to cover more area; Crown Power [40] Depending on system, Heating provided by Available (= 1) C4 Heating option provided heating by heat pump or Available (= 1) or Not (= 0) heat pump not; Carrier [41] ANSI 12.2, ASHREA noise Wall-mounted spilt unit C5 Sound rating level 66 dBA and vibration standard, max. = 66 Farhad et al. [15] Depending on system, Available (= 1) retained air or fresh air; C6 Air replenishment System uses fresh air Available (= 1) or Not (= 0) ASHRAE standard 62.1 [42]. Scale: 1 = very suitable; 2 = good appearance; C7 Aesthetics of system Scale Subjective Very suitable (= 1) 3 = acceptable; 4 = not suitable, 5 = extremely unsuitable) Depending on system, System occupies less occupies less space or not; Wall-mounted spilt unit C8 Dimensions of units space = 0.2008 max. = 0.2008 Jiayou and Yanxin [44], Camejo and Hittle [45] Depending on system, imposes lower load on System has lower load on Wall-mounted spilt unit C9 Weights of units Kg building or not; Jiayou and building = 58 max. = 58 Yanxin (2009) [44], Camejo and Hittle [45] Ease of installation Scale: 1 = Easy; C10 Scale Subjective Easy to install (= 1) or construction 3 = Medium; 5 = Difﬁcult Depending on expert opinions, scale: 1 = easy to System linked with ﬁre C11 Scale Subjective Easy to link (= 1) link; 2 = applicable to link; alarm system 3 = medium; 4 = difﬁcult to link; 5 = unable to link Scale: 1 = high; 2 = good; System’s environmental C12 Scale Subjective High (= 1) 3 = medium; 4 = low; efﬁciency 5 = poor ASHRAE Equipment Life Packaged chiller C13 28 Years System lifetime Expectancy chart, ASHRAE centrifugal max. = 28 HVAC Applications [51] Depending on expert opinions, scale: 1 = services are easily available; 2 = service available with Agent’s ability to Services are easily C14 Scale Subjective some agents; 3 = services provide services available (= 1) available after some time; 4 = difﬁcult to obtain services; 5 = services not available The VE concept considers function analysis when selecting an HVAC system with the quality criteria. The FAST technique is a common method for evaluating system function [5]. In a graphical representation, the FAST diagram leads to outputs by logical relations between system or project functions; however, the weight of functions is not calculated by the technique. The AHP, on the other hand, is a well-known way to identify methods that use pairwise weighting. This study integrated the FAST and AHP methods to determine the CW for every HVAC system criterion selection. The purpose of the CW in Sustainability 2022, 14, 2126 14 of 30 the AHP technique is to ﬁgure out how each criterion is important and how it relates to other criteria (criteria priority) [68]. The CW was identiﬁed in this study using FAST analysis to accomplish the project goal. A shortcoming of many studies is that they overlook the problems involved in calculating CW [33]. They take it for granted that decision-makers are aware of the criteria assessment. The ﬁve tasks described below can be used to determine CW in this model. 3.2.2. Step 2: Evaluate the Criteria Weight (CW) Task 1: Establish the project goal and conduct a functional analysis. The proposed HVAC systems must achieve the project’s primary goal. The main questionnaire establishes scores for each function/subfunction/criterion based on input from design experts. In the VE process, function analysis plays an important role as well. HVAC system criteria cannot be weighted until the function analysis is carried out. Task 2: Link the criteria to the functions/subfunctions/criteria. In this task, the FAST and AHP/pairwise methods are integrated. Each criterion has to be relevant to its respective function in order to achieve the integration. Figure 3 depicts the integration of the proposed model. The diagram shows how the criteria are related to the HVAC system’s functions. The function analysis with the FAST approach is represented on the left side, and the criteria results from step 1 are represented on the right side. The design experts must determine the function analysis and distribution of criteria related to the function/subfunction. Task 3: On the FAST diagram, assign weights to all functions, subfunctions, and criteria. Some criteria can be applied to many functions. Accordingly, all criteria should be allocated weights using one of the two means described below. According to Zardari, if there are three or fewer criteria being compared on one level, the point allocation technique should be used [33]. The experts used numbers to describe the CW values directly in the point allocation technique. If there were more than three criteria being compared at one level, pairwise comparison was used. Using scale factors ranging from 1 to 9, pairwise comparison uses expert judgment to assess the relative value of each criterion against the others. Each of two criteria has a value of 1 if they are equally important. If one criterion is more signiﬁcant than the other, a factor of importance degree is assigned on a scale of 2 to 9. This approach then creates a matrix and employs equations to determine the weight of each criterion, as indicated by Bhushan and Rai [69]. All functions/subfunctions/criteria are assigned a weight based on expert input by the end of this task. Tables 14–16 show the pairwise comparison matrix calculations for an ofﬁce building. In the future, assigning weights for all building types will be required in step 1, task 2. Task 4: Calculate distributed criteria weights. The following step determines where the criteria are associated with each function and subfunction. Multiply all weights in Task 3 for each path of the FAST diagram to complete this task. As indicated in Figure 3, each path can contain functions, subfunctions, and criteria. Table 17 explains the calculations of the DCW, which is calculated by Equation (4): DCW = W W W (4) (Each path) (Function) (SubFuction) (Criteria) Task 5: Calculate the CW for each criterion. The DCW values for all system criteria are assigned based on the results of the previous four steps. Because system criteria might be linked to several functions/subfunctions, there is a requirement to include all DCWs that are associated with one criterion, which reﬂects the CW using Equation (5): CW = DCW (5) (For Each Criterion) å (For all DCWs relate it to each criterion) All CW values for the total system should be equal to 1 (100%) in order to verify the computations. The last column of Table 17 shows that all CWs are equal to DCWs, as all of the criteria are linked with sole functions/subfunctions in the case of the selected criteria. Sustainability 2022, 14, 2126 15 of 32 Sustainability 2022, 14, 2126 15 of 30 pairwise comparison matrix calculations for an office building. In the future, assigning weights for all building types will be required in step 1, task 2. Figure 3. Criteria integration with FAST diagram of a building. Figure 3. Criteria integration with FAST diagram of a building. Table 14. Pairwise comparison matrix (function comparison). Table 14. Pairwise comparison matrix (function comparison). Less Energy Better Indoor Thermal Better Air Less Energy Better Indoor Better Air High High HVAC HVAC System System Qu Quality ality Less Noise Less Noise W V W ector Vector Consumption Consumption Thermal Comfort Comfort Quality Quality Less energy consumption 1 (0.125) 0.25 (0.136) 0.5 (0.1) 1 (0.125) 0.122 Less energy consumption 1 (0.125) 0.25 (0.136) 0.5 (0.1) 1 (0.125) 0.122 Better indoor thermal comfort 4 (0.5) 1 (0.54) 3 (0.6) 4 (0.5) 0.535 Better indoor thermal comfort 4 (0.5) 1 (0.54) 3 (0.6) 4 (0.5) 0.535 Less noise 2 (0.25) 0.333 (0.182) 1 (0.2) 2 (0.25) 0.221 Better air quality 1 (0.125) 0.25 (0.136) 0.5 (0.1) 1 (0.125) 0.122 1 1 1 1 1 Sustainability 2022, 14, 2126 16 of 30 Table 15. Pairwise comparison matrix (quality comparison). Easier to Install Integration and Less Space High HVAC System Suitability Less Weight on or Build Connectivity Used in W Vector and Simplest Buildability Building (Conﬁguration with Other Building and Creation) Systems Less space used in building 1 (0.25) 2 (0.286) 2 (0.286) 0.5 (0.231) 0.263 Less weight on building 0.5 (0.125) 1 (0.143) 1 (0.143) 0.333 (0.154) 0.141 Easier to install or build 0.5 (0.125) 1 (0.143) 1 (0.143) 0.333 (0.154) 0.141 (conﬁguration and creation) Integration and connectivity 2 (0.5) 3 (0.428) 3 (0.428) 1 (0.461) 0.455 with other systems 1 1 1 1 1 Table 16. Pairwise comparison matrix (buildability comparison). High HVAC HVAC System Meets High System Good System Suitability Good Long W Vector Occupants’ Requirements Quality Appearance and Simplest Sustainability Durability Buildability 0.5 High system quality 1 (0.5) 8 (0.5) 2 (0.5) 8 (0.5) 4 (0.5) 0.0625 Good appearance 0.125 (0.0625) 1 (0.0625) 0.25 (0.0625) 1 (0.0625) 0.5 (0.0625) High HVAC system 0.25 suitability and 0.5 (0.25) 4 (0.25) 1 (0.25) 4 (0.25) 2 (0.25) simplest buildability 0.0625 Good sustainability choice 0.125 (0.0625) 1 (0.0625) 0.25 (0.0625) 1 (0.0625) 0.5 (0.0625) 0.125 Long durability 0.25 (0.125) 2 (0.125) 0.5 (0.125) 2 (0.125) 1 (0.125) 1 1 1 1 1 1 3.2.3. Step 3: Calculate QW for Each HVAC System Alternative Quantifying the QW value for each HVAC alternative can be carried out after speci- fying the criteria items and CW from step 2. This computation can be achieved in three subsequence tasks. Task 1 establishes the CQW for each criterion, which were normalized in Task 2. Task 3 computes the QW for each system alternative by summing all the normalized CQW values for each HVAC alternative. Task 1: For each criterion that corresponds to an HVAC system alternative, deﬁne the CQW. Each criterion has to be measured according to international tests or other sources such as manufacturer ’s information, HVAC system technical speciﬁcation catalogs, information available from contractors or professional consultants, and other publications, as speciﬁed in the ﬁrst step [70]. The next objective is to apply these accepted tests to various systems to deﬁne the HVAC system quality categories. If a criterion is not measured, the CQW is subjectively weighed by design experts based on their experience. The value is from 1 to 5, with 1 = excellent and 5 = poor. Task 2: Normalize the CQW value for each HVAC alternative. The tests must ﬁrst be normalized to a range of 0 to 1. For each HVAC option, the sum of all CQW values should be weighted to one (equivalent to 100%). It is easier to interpret and measure CQW after it has been normalized. Linear scale transformation, max method is one way to normalize values [73]. Equations (6) and (7) are used to adjust quality and LCC in this study according to whether the quality scale is ascending (high quality means high value) or descending (high quality means low value): R = X /(X ) (6) ij ij imax Sustainability 2022, 14, 2126 17 of 30 R = (X )/X (7) ij imin ij Equation (6) is used for beneﬁt values, and Equation (7) is used for non-beneﬁcial values, where R is the normalized value of system i for criterion j, X is the criterion value ij ij of the evaluated system, X is the maximum criterion value, and X is the minimum imax imin criterion value. Table 17. Calculation of criteria weight (CW). DCW = W1 Function Subfunction Criterion W1 W2 W3 CW = DCW W2 W3 High HVAC Less energy Energy efﬁciency 0.5 0.122 1 0.061 0.061 consumption ratio quality Better indoor High HVAC thermal comfort High air volume 0.5 0.535 0.75 0.75 0.1505 0.1505 quality (spatial air cover) Better indoor High HVAC Centralized place thermal comfort 0.5 0.535 0.75 0.25 0.05 0.05 quality (Air cover for air outlet the space) High HVAC Better indoor Provide heating 0.5 0.535 0.25 0.067 0.067 thermal comfort option quality High HVAC Less noise Sound rating level 0.5 0.221 1 0.1105 0.1105 quality High HVAC Better air quality Air replenishment 0.5 0.122 1 0.061 0.061 quality HVAC suitability Aesthetics of and simplest Good appearance 0.0625 1 1 0.0625 0.0625 system buildability HVAC suitability Less space used Dimensions of and simplest 0.25 0.263 1 0.0657 0.0657 in building units buildability HVAC suitability Less weight 0.25 0.141 1 0.035 0.035 and simplest Weights of units on building buildability Easier to install HVAC suitability or build Ease of installation and simplest 0.25 0.141 1 0.035 0.035 (conﬁguration or construction buildability and creation) HVAC suitability Integration and System links with and simplest connectivity with 0.25 0.455 1 0.114 0.114 ﬁre alarm system buildability other systems More Good sustainability Environmental environmentally 0.0625 1 1 0.0625 0.0625 choice efﬁciency friendly Longer system Long durability Life time of system 0.125 0.7 1 0.0875 0.0875 life time Agent provides Agent’s ability to Long durability 0.125 0.3 1 0.0375 0.0375 good after-sale provide services service For the beneﬁcial criteria, a higher value of performance measures (such as proﬁt and quality) is desirable. For the non-beneﬁcial criteria, a lower value of performance measures (such as cost) is desirable. Task 3: Calculate the QW for each HVAC alternative. The ﬁnal quality value (QW) for each system can be derived using the CQW deter- mined before. The following calculation can compute the new QW factor by multiplying the relevant CW and CQW for each of system criterion. This relation is formulated as in Equation (8): QW = CQW CW (8) j å i j i where QW is quality weight for the system, CQW is criteria quality weight, CW is criteria weight, i is criterion number, and j is HVAC system number. Sustainability 2022, 14, 2126 18 of 30 3.2.4. Step 4: Develop a Predictive LCC Model for the HVAC System The model will include costs through the phases of the HVAC system (initial cost for purchasing the system, energy expenditure, maintenance cost). The predictive model will apply to HVAC system alternatives. After that, costs are calculated for each category (including energy and maintenance costs). An expert helped to obtain estimates for these costs for each system in our case study, then we evaluated the results by using a statistical method developed by the experts in order to obtain more accurate results. Task 1: Identify the initial costs. Initial costs are obtained from the market as the average cost for each type of HVAC system among the leading brands in Saudi Arabia. Task 2: Determine the operation costs. When choosing a system, its energy consump- tion can be determined. Then, the equation can be considered in order to include the impact of the parameters on the energy cost, such as electricity tariff, electricity consumption, operating time, system capacity, and value added tax (VAT). This relation is formulated in Equation (9): Energy Cost = Operating hours Tons of system Consumption (kw/1 ton) Electricity cost SAR 18 or (9) 32/1 kw VAT (15%) Task 3: Determine the maintenance cost by deﬁning the maintenance activities through- out the lifetime of the HVAC system. The cost of each maintenance strategy (predictive and corrective) in each HVAC system has to be determined. Each strategy is impacted by spare parts and labor cost. The water and air chiller were calculated directly based on contracts for local projects for operation and maintenance (O&M) of this system in buildings. Experts reviewed the measurements in different projects to control them and ensure the results. Table 18 shows how the costs for each component in each maintenance strategy were measured for three selected systems. Task 4: Apply the Monte Carlo simulation tool. The results of the traditional model described above were compared with the results of the Monte Carlo model by experts to de- termine the minimum and maximum of each cost category. The limits helped in generating iterations to achieve greater accuracy. The experts’ responses were essential in determining the distribution data type. The results became less risky due to the consideration of all scenarios and risks. Task 5: Identify the LCC scores with normalization. By applying Equation (2), cumula- tive costs were determined. The results are summarized in Table 19 to show the differences between HVAC systems. 3.2.5. Step 5: Calculate Value Scores This is the ﬁnal step in obtaining the result of the proposed model. The HVAC system with the highest score is selected based on it. The HVAC system value is calculated according to Equation (1). Table 20 shows example value scores. 3.3. Phase 3: Integrate the Model with BIM As discussed earlier, BIM can be integrated with external data through an API and the Dynamo application. The following tasks are applied in the model: Task 1: Model the HVAC systems. All possible alternative systems have to be modeled. This is necessary in order to specify system speciﬁcations. Task 2: Enter the system data. Values for all quality criteria have to be assigned, and cost information has to be included. It can be manually entered or connected to an external database. Task 3: Enter the project information criteria. All project data, including the weights of the criteria, have to be deﬁned according to the project function analysis. Task 4: Run the calculation program. The computation process is executed once all inputs have been entered. Then, the ﬁnal HVAC systems for the best price are obtained. All options will be ranked, and the results will be displayed. Table 21 shows the parameters used with data inputs and outputs. Sustainability 2022, 14, 2126 19 of 30 Table 18. Maintenance cost for HVAC system. Split VRF System with Components Rooftop Packaged Life Time (Years) Wall-Mounted Fan Coil Unit Cleaning (labor) min–max SAR min–max SAR min–max SAR 0.5 Preventive In + out ﬁlter replacement min–max SAR min–max SAR min–max SAR 1 Freon min–max SAR min–max SAR min–max SAR Freon ﬁlter min–max SAR min–max SAR min–max SAR Seals min–max SAR min–max SAR min–max SAR Labor cost min–max SAR min–max SAR min–max SAR Condenser fan min–max SAR min–max SAR min–max SAR Condenser fan motor min–max SAR min–max SAR min–max SAR Corrective Evaporator fan min–max SAR min–max SAR min–max SAR Evaporator fan motor min–max SAR min–max SAR min–max SAR Capacitor min–max SAR min–max SAR min–max SAR Control unit min–max SAR min–max SAR min–max SAR Labor cost min–max SAR min–max SAR min–max SAR Compressor min–max SAR min–max SAR min–max SAR Labor cost min–max SAR min–max SAR min–max SAR Total maintenance cost min (SAR) Min (SAR) Min (SAR) Min (SAR) Per Year Total maintenance cost max (SAR) Max (SAR) Max (SAR) Max (SAR) Table 19. LCC values for HVAC systems. Water Chiller with Air Chiller with Packaged System Wall-Mounted VRF System with LCC (Per Year) Fan Coil Units Fan Coil Units (Rooftop Unit) System Fan Coil Unit Initial cost SAR SAR SAR SAR SAR (per year) min Initial cost SAR SAR SAR SAR SAR (per year) max Total M&O cost SAR SAR SAR SAR SAR (per year) min Total M&O cost SAR SAR SAR SAR SAR (per year) max Rating Score Score Score Score Score (normalized) Table 20. HVAC system values. Rooftop Water Chiller with Air Chiller with Wall-Mounted VRF System with Packaged Fan Coil Units Fan Coil Units System Fan Coil Unit System Quality weight = QW score QW score QW score QW score QW score CQW CW (LCC) = Initial cost + LCC score LCC score LCC score LCC score LCC score Operating cost V = HVAC Value score Value score Value score Value score Value score system value Sustainability 2022, 14, 2126 20 of 30 Table 21. Added parameters. Parameter Name Parameter Group Parameter Names Assigned Category Parameter Type Preﬁx CR.01. Energy efﬁciency ratio CR.02. High air volume CR.03. Centralized place for air outlet CR.04. Provide heating option CR.05. Sound rating level CR.06. Air replenishment CR.07. Aesthetics of system Criteria parameters HVAC system CR.XX. Number CR.08. Dimensions of units CR.09. Weights of units CR.10. Ease of installation or construction CR.11. System linked with ﬁre alarm system CR.12. System’s environmental efﬁciency CR.13. System lifetime CR.14. Agent’s ability to provide services BC.01. Beneﬁcial BC.02. Beneﬁcial BC.03. Beneﬁcial BC.04. Beneﬁcial BC.05. Beneﬁcial BC.06. Beneﬁcial BC.07. Beneﬁcial Beneﬁt Project information BC.XX. Yes/No BC.08. Beneﬁcial BC.09. Beneﬁcial BC.10. Beneﬁcial BC.11. Beneﬁcial BC.12. Beneﬁcial BC.13. Beneﬁcial BC.14. Beneﬁcial WP.01. Energy efﬁciency ratio WP.02. High air volume WP.03. Centralized place for air outlet WP.04. Provide heating option WP.05. Sound rating level WP.06. Air replenishment Weight parameters WP.07. Aesthetics of system Project Information WP.XX. Number WP.08. Dimensions of units WP.09. Weights of units WP.10. Ease of installation or construction WP.11. System linked with ﬁre alarm system WP.12. System’s environmental efﬁciency WP.13. System lifetime WP.14. Agent’s ability to provide services Cost parameters LCC Cost HVAC system N/A Number Value output Normalized_Cost HVAC system N/A Number parameters Normalized_Quality Value 3.4. Phase 4: Apply Case Study Using the Introduced Model The case study was an ofﬁce building, used to validate the evaluation procedures. The building investigated and assessed ﬁve types of HVAC systems identiﬁed as the most commonly used in the Saudi market. The outcomes can assist decision-makers with determining which system provides the best value. 3.4.1. General Information Building name: King Saud University Endowment (KSUE) Building 13 Building type: Ofﬁce building 2 2 Building area: 20,985.20 m (225,883 ft ) Location: King Abdullah Road, Riyadh, Saudi Arabia Project life span: 30 years 3.4.2. Description Building 13 is an endowment building at King Saud University. It has an area of 208 2 3 m and volume of 52,184.21 m . Based on its function type and components, it is occupied by 735 people. The calculated results from Autodesk Revit for this case study show the Sustainability 2022, 14, 2126 21 of 30 Sustainability 2022, 14, 2126 22 of 32 building requires 768.75 tonnage of cooling. Figure 4 shows a picture of the building and its elevation in 3D. Figure 4. Case study 3D building model. (Building 13, donated by Abdulrahman A. Al Helayel.). Figure 4. Case study 3D building model. (Building 13, donated by Abdulrahman A. Al Helayel.). 3.4.3. Case Study Procedures 3.4.3. Case Study Procedures For the case study, steps 2 to 4 of the HVAC selection model were applied to select For the case study, steps 2 to 4 of the HVAC selection model were applied to select the highest rated HVAC system among the ﬁve types: water and air chiller, VRF, rooftop the highest rated HVAC system among the five types: water and air chiller, VRF, rooftop packaged rooftop, and split wall-mounted. packaged rooftop, and split wall-mounted. Step 2: Determine the CW of the ofﬁce building. Step 2: Determine the CW of the office building. The CW for the ofﬁce building was established in the model as described before. It The CW for the office building was established in the model as described before. It was determined according to expert meetings and veriﬁed by a questionnaire, as shown in was determined according to expert meetings and verified by a questionnaire, as shown Table 17. These CW values were applied to the case study because its building type is an in Table 17. These CW values were applied to the case study because its building type is ofﬁce building. an office building. Step 3: Determine the QW of ﬁve case study HVAC systems. Step 3: Determine the QW of five case study HVAC systems. Table 13 lists the CQW scales for the fourteen criteria. Each of the ﬁve identiﬁed HVAC Table 13 lists the CQW scales for the fourteen criteria. Each of the five identified systems has its own criteria value that needs to be evaluated and normalized within the HVAC systems has its own criteria value that needs to be evaluated and normalized CQW in Table 13. Table 22 presents the CQW in terms of unit value and normalized value within the CQW in Table 13. Table 22 presents the CQW in terms of unit value and nor- between 0 and 1 using Equations (6) and (7). The normalized value for criteria 3, 4, and 6 malized value between 0 and 1 using Equations (6) and (7). The normalized value for cri- is either 0 or 1 because these criteria do not have a scale. After calculating all normalized teria 3, 4, and 6 is either 0 or 1 because these criteria do not have a scale. After calculating values of CQW for all fourteen criteria of the ﬁve HVAC systems used in this case study, all normalized values of CQW for all fourteen criteria of the five HVAC systems used in QW for each system can be determined according to Equation (8) by multiplying each this case study, QW for each system can be determined according to Equation (8) by mul- CQW HVAC system type with the corresponding CW in Table 17 and summing all values tiplying each CQW HVAC system type with the corresponding CW in Table 17 and sum- for each system. For example, the QW of water chiller and fan coil unit 450T is 0.59896268, ming all values for each system. For example, the QW of water chiller and fan coil unit shown in the last row of HVAC system type (ﬁfth column) according to this calculation: 450T is 0.59896268, shown in the last row of HVAC system type (fifth column) according to this calculation: 0.59896268 = 0.46222222 0.061 + 0.74103704 0.1505 + . . . + 0.25 0.0375 0.59896268 = 0.46222222 × 0.061 + 0.74103704 × 0.1505 + … + 0.25 × 0.0375 Step 4: Develop a predictive LCC model for the case study. This step includes three tasks: Table 22. Numerical values of selected criteria + normalized classification matrix. Task 1: Identify the initial costs. The predictive model calculates the initial cost among the market prices to purchase Water Air Chiller and procure the system and the contractor Rooftop ’s work Split Wall- price to constr VRF and uct the entire system. Optimal Chiller and and Fan CW (from For some systems, such as VRF and chillers, the price is in Saudi Arabian Riyal (SAR) per Criteria Unit Packaged Mounted Fan Coil Value Fan Coil Coil Unit Table 12) ton to construct the system. This price includes procuring and constructing the system to 25T 1.5T Unit 17.5T Unit 450T 113T commission the user. 36 (btu/W.h) 16.64 9.7 10.55 12.4 14.15 EER Normalize on 0.061 0.46222222 0.2694444 0.2930556 0.3444444 0.3930556 scale Sustainability 2022, 14, 2126 22 of 30 Tasks 2 and 3: Determine the O&M cost. The model divides the system O&M cost into two categories: Chillers: Cost calculations obtained for air and water systems will depend on King Saud University Endowment operation and maintenance project data. The data contain the SAR price per ton for the entire system. The price is based on the current utility cost (electricity, water), O&M contractor crew, spare parts, chemicals, and inﬂation of 3% each year. Split, packaged, and VRF: The calculations for this category are divided into the maintenance strategy cost (predictive, corrective), operation cost, and inﬂation of 3% each year. Table 22. Numerical values of selected criteria + normalized classiﬁcation matrix. Water Chiller Air Chiller Rooftop Split Wall- VRF and Fan Optimal CW (from Criteria Unit and Fan Coil and Fan Coil Packaged Mounted Coil Unit Value Table 12) Unit 450T Unit 113T 25T 1.5T 17.5T 36 (btu/W.h) 16.64 9.7 10.55 12.4 14.15 0.061 EER Normalize on 0.46222222 0.2694444 0.2930556 0.3444444 0.3930556 scale 189,000 CFM 140,056 35,588 9200 512 5740 Air volume 0.1505 Normalize on 0.74103704 0.1882963 0.0486772 0.002709 0.0303704 scale Wall- Central place Central place Central place Center place mounted (more (more (more (more units (less covered area) covered area) covered area) covered area) 0.05 Centralized air diffuser covered area) Normalize on 1 1 1 0 1 scale 1 Fresh air Fresh air Fresh air Retained air Fresh air Air replenishment 0.067 Normalize on 1 1 1 0 1 scale 66 dBA 135 130 77 99 114.4 Sound rating level 0.1105 Normalize on (dBA) 0.425 0.4666667 0.9083333 0.725 0.5966667 scale 1 Not available Not available Not available Available Available Heating option (for 0.061 Normalize on cooling season) 0 0 0 1 1 scale 1 subjective 2 3 2 4 1 Aesthetics of system 0.0625 Normalize on (subjective evaluation) 0.75 0.5 0.75 0.25 1 scale 0.2008 m3 46.033 23.829 9.804 0.36193 5.998 Dimensions of system 0.0657 3 Normalize on (m ) 0.32697888 0.6530326 0.8589822 0.9976339 0.9148712 scale 58 kg 9875 5253 959 69.6 1912 Weight of system (kg) 0.035 Normalize on 0.34814077 0.6550465 0.9401726 0.9992297 0.8768924 scale 1 subjective 4 3 3 1 2 Ease of installation 0.035 Normalize on 0.25 0.5 0.5 1 0.75 scale 1 subjective 2 2 1 3 3 System linked with ﬁre 0.114 Normalize on alarm system 0.75 0.75 1 0.5 0.5 scale 1 subjective 1 2 3 3 3 System’s environmental 0.0625 Normalize on efﬁciency 1 0.75 0.5 0.5 0.5 scale 28 years 20 20 15 15 15 System lifetime 0.0875 Normalize on 0.55555556 0.5555556 0.2777778 0.2777778 0.2777778 scale 1 subjective 4 4 2 1 2 Agent’s ability to 0.0375 Normalize on provide services 0.25 0.25 0.75 1 0.75 scale Q + F cores 0.59896268 0.5182834 0.5939699 0.4637295 0.5927076 Sustainability 2022, 14, 2126 24 of 32 The predictive model calculates the initial cost among the market prices to purchase and procure the system and the contractor’s work price to construct the entire system. For some systems, such as VRF and chillers, the price is in Saudi Arabian Riyal (SAR) per ton to construct the system. This price includes procuring and constructing the system to com- mission the user. Tasks 2 and 3: Determine the O&M cost. The model divides the system O&M cost into two categories: • Chillers: Cost calculations obtained for air and water systems will depend on King Saud University Endowment operation and maintenance project data. The data con- tain the SAR price per ton for the entire system. The price is based on the current utility cost (electricity, water), O&M contractor crew, spare parts, chemicals, and in- flation of 3% each year. • Split, packaged, and VRF: The calculations for this category are divided into the Sustainability 2022, 14, 2126 23 of 30 maintenance strategy cost (predictive, corrective), operation cost, and inflation of 3% each year. Task 4: Apply the Monte Carlo simulation tool. Task 4: Apply the Monte Carlo simulation tool. For the O&M costs, the case study relies on the current prices for some brands in the For the O&M costs, the case study relies on the current prices for some brands in Saudi market, which is not entirely accurate because we need to determine the limits (min- the Saudi market, which is not entirely accurate because we need to determine the limits imum and maximum values) for each cost category as well. Therefore, the price possibil- (minimum and maximum values) for each cost category as well. Therefore, the price ities can be covered to have more accurate results. In this case, using Monte Carlo simu- possibilities can be covered to have more accurate results. In this case, using Monte Carlo lation can be helpful. As shown in Figure 5, the determinants of O&M costs for each simulation can be helpful. As shown in Figure 5, the determinants of O&M costs for each HVAC system were determined. For this, 1000 iterations on an Excel sheet were executed HVAC system were determined. For this, 1000 iterations on an Excel sheet were executed to obtain accurate values. to obtain accurate values. Operation & Maintenance Costs SAR/1Ton.1hr SAR 30 Packaged system SAR 25 SAR 20 Spilt wall mounted system SAR 15 VRF SAR 10 SAR 5 Water chiller SAR 0 Air chiller 0 102030 Years Figure 5. O&M costs for HVAC systems using the Monte Carlo technique. Figure 5. O&M costs for HVAC systems using the Monte Carlo technique. Each system lifetime listed in the ASHREA standard is considered as part of the ini- Each system lifetime listed in the ASHREA standard is considered as part of the tial cost. Lifetime is determined as 20 years for chillers (water, air) and 15 years for pack- initial cost. Lifetime is determined as 20 years for chillers (water, air) and 15 years for aged, split, and VRF. Table 23 shows the IC calculation for each system based on Monte packaged, split, and VRF. Table 23 shows the IC calculation for each system based on Monte Carlo analysis. Carlo analysis. Step 5: Calculate value scores. Because the model was programmed with a BIM model (using Revit software) for selection of HVAC systems, this step can be calculated directly. All weights and values for the criteria were entered with the model, and were quickly imported into Dynamo from an Excel spreadsheet. In addition, the cost of the system’s LCC was entered for the case study information. The model directly determines the quality scores and values and compares the highest and lowest value alternatives using Equation (1), as shown in Table 24. 3.4.4. Case Study Analysis and Discussion As seen in Table 24, the case study results show that water chiller, VRF, and packaged systems have essentially identical quality results. However, air chiller and split wall- mounted systems have lower scores. While the cost criteria for the air chiller, packaged, split wall-mounted, and VRF systems are superior to the those for the water chiller, the lower cost gives the system more value in the total score. The value score of the water chiller has the highest equivalent between quality and cost. A large difference in LCC impacts the value index of the selected option (water chiller). The case study result was compatible with the selected case study option. It is noted that the quality levels of the ﬁve HVAC alternatives were close to each other. The difference in LCC strongly impacts the value index of the selected option. The LCC forecast model was veriﬁed by comparing O & M Costs Sustainability 2022, 14, 2126 24 of 30 it with the actual O&M contract data of the case study, a KSUE ofﬁce building in Riyadh, Saudi Arabia. Riyadh has dry weather; thus, humidity did not affect the cooling loads considered in the BIM system. Ge et al. [74] studied the impact of different climate zones on the energy performance of business buildings in China. Mendes et al. [75] investigated the effects of humidity by comparing three cities (Singapore, Seattle, and Phoenix). However, the proposed HVAC model is not affected by this aspect, as the cooling load is an input to the model, which should consider any humidity effects. Table 23. Initial cost for HVAC systems using the Monte Carlo technique. Years Package Split VRF Water Chiller Air Chiller 1 89,951.713 3515.312 65,593.985 2,252,460.707 310,525.19 15 136,060.0368 5317.2248 99,216.788 - - 20 - - - 3,949,703.484 544,507.8 30 211,977.1041 8284.063 15,4576.52 - - Total IC for 437,988.8539 17,116.6 319,387.3 6,202,164.191 855,033 30 years Table 24. Results of evaluation from BIM model. Water Chiller Air Chiller Rooftop Split Wall- VRF and System Type and Fan Coil and Fan Coil Packaged Mounted Fan Coil Unit 450T Unit 113T 25T 1.5T Unit 17.5T Q + F Scores 0.59896268 0.5182834 0.5939699 0.4637295 0.5927076 Norm LCC 0.12744815 0.530197473 0.922395132 0.805415474 1 V score 4.699657704 0.977528989 0.643943012 0.575764329 0.5927076 Selected system 3.5. Phase 5: Model Validation and Questionnaires This study’s ﬁrst data-gathering instrument was a self-administered questionnaire. The questionnaire was used for various reasons, including to allow the data to be standard- ized and analyzed more straightforwardly, and to allow information to be acquired quickly from a signiﬁcant number of people. 3.5.1. Questionnaire Design In this research, two questionnaires were designed. The ﬁrst was the main question- naire, which was distributed to 21 experts. Through interviews, three experts reviewed the LCC results based on the external data (project contract) to perform the second validation. Table 25 provides a summary of the questionnaires. 3.5.2. Likert Scale A Likert scale was used to create the main questions (Table 26). The questions were graded on a scale of 1 to 5, with 1 being the lowest and 5 the highest. The score can be determined by using the weighted points on the Likert scale according to Emerson [76], with Equation (10): Score = i ni (10) i=1 where i is the Likert scale (i = 1, 2, . . . , 5), ni is the number of respondents who chose scale i, and N is the total number of respondents. Scores of 4 or greater than or equal were chosen using this procedure. Sustainability 2022, 14, 2126 25 of 30 Table 25. Summary of questionnaires. Questionnaire Respondents Topics Category VE challenges Setting HVAC system selection criteria Main 21 Evaluating results of HVAC criteria weight measurement Determining results of criteria weight ranking Evaluating outcomes of spare parts, labor, and operation Experts 3 and maintenance costs for HVAC systems Table 26. VE aspects, main questionnaire responses, part 2. Frequency 3 Neither Total 1 Strongly 5 Strongly Select No VE aspects 2 Disagree Agree nor 4 Agree Total Likert Disagree Agree Score 4 Disagree Points I applied VE in one of my 1 2 3 4 6 6 21 3.52 projects before I’m welcome to apply VE in 2 1 0 2 2 16 21 4.52 X construction projects Applying VE in construction 3 2 4 4 7 4 21 3.33 projects has some difﬁculties In order to keep VE more straightforward to use, its process needs to have 4 1 0 5 6 9 21 4.04 X approximately uniﬁed criteria for selecting construction materials By including approximate criteria for selecting materials 5 1 1 1 7 11 21 4.24 X in BIM, VE becomes easier to apply Applying VE in HVAC 6 systems has more value than 1 3 4 9 4 21 3.57 other construction materials 3.5.3. Main Questionnaire The main questionnaire was aimed at professionals working in HVAC construction in Saudi Arabia, was designed with the following components. Part 1: General information This part was used to obtain information about the respondents. There were 21 re- spondents. Their backgrounds included mechanical engineer (52.4%), civil engineer (19%), QC mechanical engineer (14.3%), and electrical engineer (14.3%). They had experience in various areas, including O&M (33.3%), contracting (19%), consulting (19%), supply (9.5%), building use (9.5%), and other (9.5%). In terms of length of experience, 38.1% 10–20 years, 38.1% had 1–5 years, 19% had 5–10 years, and 4.8% had work experience of more than 20 years. The statistics of the 21 respondents were considered sufﬁcient for the veriﬁcation process, as the authors made efforts to communicate with them by having direct calls and meetings to clarify the questions and having more reliable information when specialized expertise was lacking. Part 2: VE aspects The questionnaire respondents were asked about VE to conﬁrm the need for approxi- mately uniﬁed criteria for HVAC selection and modeling by BIM for the VE process. The results in this part showed total scores greater than 4, which indicates agreement with the context, as shown in Table 26. Sustainability 2022, 14, 2126 26 of 30 Based on Table 26, while the questionnaire respondents did not usually apply VE to their projects, they welcomed the chance to apply it in future projects. The results show several important points; the need to have uniﬁed criteria for the HVAC selection process and to include the process on a modeling platform such as BIM, had high scores. Among the respondents, 43% (9 out of 21) and 29% (6 out of 21) strongly agreed and agreed, respectively, with unifying the HVAC criteria. Several respondents (23%, 5 out of 21) chose not to decide. With regard to modeling the HVAC selection process, 52% (11 out of 21) and 33% (7 out of 21) of the respondents strongly agreed and agreed, respectively; these high agreement percentages conﬁrm the need for uniﬁed criteria in the selection and modeling process, which supports the goals of this research. Part 3: Uniﬁed and conﬁrmed criteria by respondent satisfaction level The questionnaire respondents were asked whether or not they agreed with the selected criteria. The results are shown in Table 27. Table 27. VE aspects, main questionnaire responses, part 2. Frequency 3 Neither Total 1 Strongly 5 Strongly Select No VE aspects 2 Disagree Agree nor 4 Agree Total Likert- Disagree Agree Score 4 Disagree Points Satisfaction level 1 0 0 3 6 12 21 4.43 X regarding these criteria Based on Table 27, the 14 chosen criteria obtained a high conﬁrmation score by the respondents; speciﬁcally, 57% (12 out of 21) strongly agreed with the 14 criteria and 29% agreed, further conﬁrming the need for uniﬁed criteria. Only 14% neither agreed nor disagreed, and 0% disagreed or strongly disagreed. 4. Conclusions The choice of HVAC system has a direct impact on the design value. VE is a process for enhancing quality and functionality and of reducing cost. This paper proposes a systematic approach to selecting the HVAC system with the highest value. A literature review of relevant studies was presented. Fourteen criteria affecting the choice of HVAC systems were identiﬁed, with a good level of satisfaction. The criteria were validated by an HVAC expert and veriﬁed by 21 respondents with a high level of satisfaction. The criteria were weighted in terms of ranking (CW) and quality (QW). The CW for the fourteen identiﬁed HVAC criteria was established for one building type, an ofﬁce building. The integrated AHP, FAST, and pairwise methods were utilized in the CW evaluation. For the QW, all fourteen criteria (subjective and objective) were measured according to standard tests and subjective evaluation measures; these QW values can be used to evaluate most of HVAC types. The QW measurement methods were established based on input from HVAC specialists and veriﬁed using a questionnaire. LCC is important in determining the HVAC value index, as it impacts operation and maintenance costs. Thus, the proposed model utilized expert knowledge combined with the Monte Carlo technique to establish a forecasting model of the HVAC LCC. This model was veriﬁed by comparing the forecast results with actual contract data using a case study of a King Saud University Endowment ofﬁce building in Riyadh, Saudi Arabia. In addition, the proposed model was programmed within the BIM model utilizing an API and the Dynamo application with Revit software. In the ﬁnal part of the study, the introduced automated model was applied to the case study ofﬁce building. The case study included an analysis and comparison of ﬁve HVAC types, and the water chiller and fan coil 450T unit was the most valuable alternative. The case study result was compatible with the selected case study option. It should be noted that the quality levels of the ﬁve HVAC alternatives were close to each other, and differences in LCC strongly impacted Sustainability 2022, 14, 2126 27 of 30 the value index of the selected option. The proposed model was designed according to ofﬁce building needs and performance. Future research could generate additional building types in order to cover other HVAC functions in the selection process. In addition, the HVAC selection model only considered options accepted by designers and which met the minimum owner/country standards within BIM. Future research could be developed in order to eliminate any BIM materials that are not accepted by designers according to special criteria. Author Contributions: Conceptualization, K.S.A.-G.; Data curation, M.A.A.-G.; Formal analysis, M.A.A.-G.; Funding acquisition, K.S.A.-G.; Investigation, M.A.A.-G. and K.S.A.-G.; Methodology, M.A.A.-G. and K.S.A.-G.; Project administration, K.S.A.-G.; Resources, K.S.A.-G.; Supervision, K.S.A.- G.; Validation, M.A.A.-G.; Writing—original draft, M.A.A.-G.; Writing—review and editing, K.S.A.-G. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Deanship of Scientiﬁc Research, King Saud University. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data in this paper were taken from other studies, as this is a review paper. The raw data supporting the ﬁndings of this paper are available on request from the corresponding author. Acknowledgments: The authors thank the Deanship of Scientiﬁc Research, King Saud University, for funding and supporting this research through the initiative of Graduate Students Research Support. We thank the Saudi Standards Metrology and Quality Organization for its support. We thank all participants who shared their knowledge to validate and verify this study. Conﬂicts of Interest: The authors declare no conﬂict of interest, ﬁnancial or otherwise. Abbreviation AHP Analytical hierarchy process API Application programming interface ASHREA American Society of Heating, Refrigerating and A-C Engineers BES Building energy simulation BIM Building information modeling CW Criteria weight dBA Decibel EER Energy efﬁciency ratio FAST Function analysis system technique IC Initial cost ISO International Organization for Standardization LCC Life cycle cost MCDM Multiple criteria decision making MEPS Mechanical, electrical, and plumbing systems NLP Neuro-linguistic programming O&M Operation and maintenance QCW Quality criteria weight QW Quality weight SASO Saudi Standards, Metrology, and Quality Organization SWARA Stepwise weight assessment ratio analysis VE Value engineering VRF Variable refrigerant ﬂow WASPAS Weighted additive sum product assessment References 1. Omer, A.M. Energy, environment and sustainable development. Renew. Sustain. Energy Rev. 2008, 12, 2265–2300. [CrossRef] 2. Pérez-Lombard, L.; Ortiz, J.; Pout, C. 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Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection

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ISSN: 2071-1050
DOI: 10.3390/su14042126
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Sustainability – Multidisciplinary Digital Publishing Institute

Published: Feb 13, 2022

Keywords: value engineering; quality; AHP; FAST; BIM; Monte Carlo; HVAC system; life cycle cost

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Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection

Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection

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Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection

Integrated Value Engineering and Life Cycle Cost Modeling for HVAC System Selection

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