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The purpose of this research is to conduct a Systematic Literature Review to identify organizational excellence methodologies (OEMs) from the state of the art literature, classify them based on their business sector, generate a unified list of organizational excellence (OE) critical success factors (CSFs), and propose future research agenda. A comprehensive analysis conducted on publications/year, publications/journals, journals’ rank, research methods, business sector, publications’ research area, and much more. The analysis reveals the identification of 46 OEMs, a unified list of 47 OE CSFs, and proposing future research agenda that include testing OEMs in the same business sector but in different countries, regions, or even different business sectors; conducting longitudinal studies on OEMs research scope; developing OEMs for the public sector and NPOs; studying the OE aspects in the MENA region; the researchers from the MENA, Africa, Malaysia, China, and the USA should put more effort to contribute to the OE scope; exploring the OE CSFs, barriers, and challenges on the different levels, business sectors, and geographical locations; testing the importance of the unified list of CSFs for organizational performance; developing a methodology to facilitate OEMs adaptation process; integrating some of the OEMs that never integrated before and test their impact on organizations’ performance; integrating the sustainability concept with the BEMs or OE concept; studying the OE applications in the new era of digitization, globalization, the Internet of Things, and industry 4.0; and proposing a methodology or framework to maintain an excellent performance level beyond the implementation stage.

The Internet of Things (IoT) is currently the main enabler of smart services, where network communication links physical objects (embedded Things), such as a sensor with a main backend server, and allows the collection and exchange of data. Therefore, it is very important to maintain high availability of smart services, especially critical services, in case any failure of the objects occurs. In this paper, we address the different business continuity (BC) approaches that can be implemented in IoT services. An assessment of the vulnerabilities and threats of IoT services is essential for containing damage and continuing services during a crisis. There is a lack of frameworks and guidelines that address the BC of IoT services. Therefore, in this paper, we review and analyze the different types of IoT architectures and risks associated with them. In addition, we analyze many use cases and different types of standards, guidelines, policies and frameworks of BC that can outfit our final framework. As a result, the analysis outcomes are used to propose a BC framework for the IoT. The proposal explains different types of IoT architectures along with different types of BC measurements for IoT services. Finally, we implement our proposed framework with one of the real IoT service use cases.

Business process management (BPM) is one of the effective performance management methodologies used in managing process-oriented organizations. BPM was adopted by many organizations and impressive results were achieved. However, BPM still in its infancy and many issues yet to be resolved. Having a unified list of the BPM critical success factors (CSFs) and BPM principles considered one of the important research areas. The literature review showed that despite the majority of BPM principles and CSFs are the same or there are minor differences between them, different terminologies were used to describe them. The literature review showed also that the methodologies used for BPM implementation were either very old, it does not cover the human interaction with BPM systems (BPMS), or it describes BPM methodology partially. Therefore, the main objectives of this research are building insights about BPM’s most recent developments, unifying BPM principles and CSFs and proposing a comprehensive BPM. The literature was analyzed to extract BPM’s developments. Moreover, the mapping process was used to propose a unified list of BPM CSFs and BPM principles. A critical success principles (CSPs) name was given to the unified list. 22 CSPs were identified, based on the nature of CSPs and implementation level, CSPs were classified into three main areas or levels namely strategic, supportive and operational CSPs. Out of 22 CSPs, 36.5% of CSPs were classified as a strategic CSPs, 45.5% of CSPs were classified as operational CSPs, and only 18% were classified as a supportive CSPs. A comprehensive BPM methodology was proposed, the proposed methodology combining the steps of generic BPM methodologies and BPMS methodologies and it is unifying the terminologies used in the reviewed methodologies. Pros and cons of the proposed methodology discussed in this research. The implications of this research can be seen in both theoretical and practical sides. For the theoretical side, the researchers can see the most recent developments in the scope of BPM, summarized in this research, and build on it to conduct future research. The proposed CSPs can be further analyzed to find the relationship between CSPs and how each one of them can affect BPM implementation. The proposed BPM methodology can be tested by applying it to the different business sectors and measure organizations’ performance during implementation stages. For the practical side, the proposed methodology can provide a guide for managers and organization leaders about the right steps to be followed during implementing BPM and conducting BPM projects. Moreover, CSPs can guide BPM project managers, organization leaders, and business excellence units to focus their efforts on the significant improvement areas and actions to be taken on strategic and operational levels.

Due to the advancement of technology that allows organizations to collect, store, organize and use data information system for efficient decision making (DM), a new horizon of supply chain performance evaluation starts. Today, DM is shifting from “information-driven” to “data-driven” for more precision in overall supply chain performance evaluation. Based on the real-time information, fast decisions are important in order to deliver product more rapidly. Performance evaluation is critical to the success of the supply chain (SC). In managing SC, there are many decisions to be taken at each level of multi-criteria decision making (MCDM) (short-term or long-term) because of many decisions and decision criteria (attributes) that have an impact on overall supply chain performance. Therefore it is essential for decision makers to know the relationship between decisions and decision criteria on overall SC performance. However, existing supply chain performance models (SCPM) are not adequate in establishing a link between decisions and decisions criteria on overall SC performance. Most of the decisions and decision attributes in SC are conflicting in nature and performance measure of different criteria (attributes) at different levels of decisions (long-term and short-term) is different and makes it more intricate for SC performance evaluation. SC performance heavily depends on how well you design your SC. In other words, it is quite difficult to improve overall SC performance if decisions criteria (attributes) are not embedded or considered at the phase of SC design. The connection between the SC design and supply chain management (SCM) is essential for effective SC. Many companies such as Wal-Mart, Dell, etc. are successful companies and they achieve their success because of their effective SC design and management of SC activities. The purpose of this thesis is in two folds: First is to develop an integrated knowledge base system (KBS) based on Fuzzy-AHP that establish a relationship between decisions and decisions criteria (attributes) and evaluate overall SC performance. The proposed KBS assists organizations and decision-makers in evaluating their overall SC performance and helps in identifying under-performed SC function and its associated criteria. In the end, the proposed system has been implemented in a case company, and we developed a SC performance monitoring dashboard of a case company for top managers and operational managers. Second to develop decisions models that will help us in calibrating decisions and improving overall SC performance.

Most of smart services are depending on Internet of Things (IoT) where network of physical objects or (Things embedded with software), electronics, sensors, and network connectivity, which allows these objects to exchange and collect data. Therefore, the high risk of discontinuity such services is very critical when one of these objects goes down in any circumstances. In this paper, a business Continuity management (BCM) approach for IoT can used for IoT services. Where Connectivity, Hardware, Middleware and Visualization are the main function of IoT services, which must addresses the risk of each elements through look at threats and vulnerabilities, and provide the suitable mitigations or work around helps those elements continue the usual work during any emergency or crisis. Using a case study of one of Dubai governmental entities will identify the directions of major root cause failure of IoT elements. The importance of this approach is to establish the BCM framework of IoT public service to gain a high performance activity during emergency.

Globalization and environmental regulations force organizations and producers to adopt sustainability in every aspect of their business. The concept of sustainability in manufacturing is now achieving maturity; however, there is still an opportunity to explore sustainability in perishable food items. The growth of population worldwide increased the amount of waste produced by the food industries. Enterprises worldwide use procedures to overcome the disposing of perishable waste into landfills, which has noticeable impacts on the environment and the business itself. However, these procedures may not be sufficient and lead to disturbance of the ecosystem. Therefore, the purpose of this article is to develop a framework to conduct experiments using Design of Experiment (DOE) to produce fertilizer using expired doughnuts from a well-known sweet bakery company in the United Arab Emirates. Firstly, we will develop a framework, implement waste management on perishable products such as doughnuts, and apply environmental, economic, and social development through recycling and composting it into fertilizers to be used for agriculture needs. Secondly, to study the impact of different parameters such as water, sand, doughnuts in different percentages on plant growth and survival. Results show that wasted doughnuts are suitable for fertilizer and the best plant due to interaction between all three factors: commercial fertilizer percentage, doughnuts percentage, and doughnuts size.

AHP applied to decision making of automotive industry supplier selection.Use of AHP in supplier selection gives decision maker confidence of consistency.Sensitivity analysis to check the robustness of the supplier selection decision.Proposed approach divides complex decision making into simpler hierarchy. PurposeThe purpose of this paper is to propose a decision support model for supplier selection based on analytic hierarchy process (AHP) using a case of automotive industry in a developing country of Pakistan and further performs sensitivity analysis to check the robustness of the supplier selection decision. MethodologyThe model starts by identifying the main criteria (price, quality, delivery and service) using literature review and ranking the main criteria based on experts' opinions using AHP. The second stage in the adopted methodology is the identification of sub criteria and ranking them on the basis of main criteria. Lastly perform sensitivity analysis to check the robustness of the decision using Expert Choiceź software. FindingsThe suppliers are selected and ranked based on sub criteria. Sensitivity analysis suggests the effects of changes in the main criteria on the suppliers ranking. The use of AHP in the supplier selection gives the decision maker the confidence of the consistency and the robustness throughout the process. Practical implicationsThe AHP methodology adopted in this study provides managers in automotive industry in Pakistan with the insights of the various factors that need to be considered while selecting suppliers for their organizations. The selected approach also aids them in prioritizing the criterion. Managers can utilize the hierarchical structure of adopted supplier selection methodology suggested in this study to rank the suppliers on the basis of various factors/criteria. Originality/valueThis study makes three novel contributions in supplier selection area. First, AHP is applied to automotive industry and use of AHP in the supplier selection gives decision maker the confidence of the consistency. Second, sensitivity analysis enables in understanding the effects of changes in the main criteria on the suppliers ranking and help decision maker to check the robustness throughout the process. Last, we find it important to come with a simple methodology for managers of automotive industry so that they can select the best suppliers. Moreover, this approach will also help managers in dividing the complex decision making problem into simpler hierarchy.

Management of supply chain (SC) is becoming more challenging with every passing day due to high competition, globalisation, and digitalisation because of the recent adoption of internet of things (IoT) technologies in order to increase supply chain visibility. Due to this fact, importance of supply chain performance measurement systems (SCPMS) has been increased significantly. To cope with these challenges and remain competitive, organisations are keen to evaluate SC performance more precisely. Therefore, this paper adopts a qualitative review methodology to find out if existing SCPMS are in line with the current emerging technology trends of managing SC and measuring SC performance and if not, what will be the characteristics of future SCPMS. Results show particularly that existing SCPMSs are not adequate to cope with the complexity and the technology advancement observed in supply chain management as a smart way for measuring modern SC performance is needed. Finally, this study proposes a conceptual supply chain performance measurement (SCPM) framework to fill the identified research gaps.

Manufacturing systems is one of the main pillars of the global economy and there is a continuous effort to make it more advanced, more sustainable, and more user-friendly. Toward this direction, the concept of computer-integrated manufacturing (CIM) invented. CAD-CAPP-CAM-CNC systems' integration considered as prerequisite for CIM to be exist. Data exchange format was one of the main systems' integration obstacles due to the lack of standardization, or in other words, lack of effective data exchange format. Therefore, ISO organization started STEP 10303(Standard for the Exchange of Product Data model) project in 1994 to create a generic standard for data exchange on different levels. STEP-NC (or ISO 14649) developed specifically for data exchange between CAD, CAM, CAPP, CNC and other corporate levels. Many researchers stated that STEP-NC format is the future solution to overcome all data exchange obstacles as it has provide a bi-directional information flow and offer the possibility of dynamic changes on the design models. However, attempts to embed STEP-NC format in manufacturing systems still at the early stage. On the other hand, in last three decades, the global warming theory reported and many researchers focused their efforts to study the sustainability concept. The objective of this paper is to prove the novelty of having an integrated system by means of STEP-NC format for data exchange and in same time generating plans by considering sustainability principles. 59 papers reviewed for the period between 2001 and 2017. Authors were able to prove the novelty of the aforementioned approach as well as finding many other research gaps.

Electro discharge machining (EDM) process need to be optimized when a new material invented or even if some process variables changed. This process has many variables and it is always difficult to get the optimum set of variables by chance. Therefore, an optimization process need to be conducted considering different combinations of machining parameters as well as other variables even if the process were optimized for a certain set of variables. Optimization of the EDM process for machining stainless steel 304 (SS304) (ASTM A240) was studied in this paper. Signal-to-noise ratio (S/N) was calculated for each performance measures, and multi response performance index (MRPI) was generated using fuzzy logic inference system. Optimal machining parameters for machining SS304 materials were identified, namely current 10, pulse on time 60 μs, and pulse off time 35 μs. Analyses of variances (ANOVA) method was used as well to see which machining parameter has significant effect on the performance measures. The result of ANOVA indicates that pulse off time and current are the most significant machining parameters in affecting the performance measures, with the pulse off time being the most significant parameter.

Warehouse performance evaluation is the measurement of efficient use of warehouse space, customer satisfaction level, quality of goods stored and transport, level of inventory and environmental friendly delivery. Managers and decision makers are keen to know very rapidly which decisions at what level need extra attention and have more impact on overall warehouse performance. In this paper, we propose a Fuzzy-AHP integrated approach that incorporates the linkage between the operational and strategic criteria to generate an overall warehouse performance measurement system. A numerical example illustrates the uses of the proposed model for Warehouse performance evaluation.

QFD is a well-known tool that forms a cross-functional planning process to transform customers' needs into detailed requirements. However, it is not that famous in the field of smart applications since technical people usually rely on customer relationship management people to identify their customers' needs and work accordingly. This article describes how public sector entities can use QFD to identify and prioritize smart service applications' characteristics, map them to customer needs and cascaded them down to a lower operational level which is the technical processes. Using a case study of one of Dubai public entities, the process of multi stages or phases has led to identify the importance of using QFD in identifying customers needs of smart services and the main technical processes to enhance them. Modifications have been introduced to the tool to suit the public sector characteristics. This research marks the importance of this tool to the public sector to improve its service similar to the private sector.

This paper proposes an automated decision-support system for conceptual design of mechanisms for function-generation design tasks. The developed system involves a library of function shapes and a knowledgebase of mechanism topologies. For each function shape, the topologies are assessed using kinematic and non-kinematic criteria and the assessments are stored in the knowledgebase. The analytic-hierarchy process (AHP) is employed to provide the user with a prioritized list of candidate design solutions. Sensitivity analysis can be performed by the system to test the prioritization for robustness. Feasibility of the system is demonstrated on a selected set of function shapes and mechanism topologies.

This paper describes a web-based Decision Agent (DA) that provides a customer-oriented approach for selecting products in online orders. The proposed approach is focused on enhancing the front-end of company's business portal by segmenting prospective online customers and directing them to use decision modules that improve user perception in terms of effort, accuracy, and acceptance. The user's Consistency Ratio (CR) in evaluating the attributes of online products is used to categorize prospected users and to direct them to proceed with one of three decision modules, Analytical Hierarchy Process (AHP), Simple Multi-Attribute Rating Technique (SMART), and Direct Scaling Method (DSM). The proposed approach is applied to an online cellular phone selection case study. Experimental results showed the fit of assigned decision modules to customer classes where users made smart phone selections with less effort and higher reported convenience and satisfaction. The approach can be tailored for other online products and can be integrated into the websites of producers and online stores in a wide range of business applications.

Birth weight is a key public health indicator that needs to be monitored regularly. However, in the United Arab and worldwide, there is currently no systematic procedure for monitoring shifts or trends in the mean and variability of birth weight at a national level. For this purpose, it is proposed to use statistical process control charts (SPC). This is illustrated through developing SPC charts for monitoring the birth weight of UAE nationals. The developed control charts indicated that the birth weight of UAE nationals is in statistical control. The national mean birth weight, standard deviation of birth weights, percentage of low birth weight, and percentage of high birth weight were estimated to be 3.208 kg, 0.445 kg, 5.59%, and 0.19%, respectively.

Specific applications of fuzzy logic in project management are relatively few in comparison to other application areas. The criteria of project cost, project time, and project quality may be considered as project management internal measures of efficiency. The objective of this research is to present an approach that employs fuzzy decision making (FDM) to combine these three measures into one measure namely the project management internal efficiency (PMIE) which should represent an overall estimate of how well the project was managed and executed. The proposed approach for the evaluation of PMIE is illustrated on a case study. A fuzzy decision making system is designed and implemented using the MATLAB software for the evaluation of the PMIE The methodology and procedure proposed in this research may be easily implemented by project management organizations. The evaluation of PMIE can serve for project managers and for project organizations as an indicator for the level of achievement of the project management internal objectives. PMIE may help in the evaluation of the performance of project teams.

Machining processes are complex and highly dynamic systems that can have many variables affecting the desired results. Fuzzy modeling proved to be effective in modeling such complex systems. Down milling machining process of Alumic-79 was modeled in this paper using the adaptive neuro fuzzy inference system (ANFIS) to predict the effect of machining variables (spindle speed, feed rate, depth of cut, and number of flutes) on the surface finish (represented by the surface roughness) of Alumic-79 in order to improve and increase its range of application. Optimum surface roughness of 0.224 μm is achieved for the four flutes at the spindle speed of 2000 rpm, feed rate of 0.06 mm/tooth, and depth of cut of 2 mm. In the meantime, it was found for the two flutes that the minimum surface roughness of 0.327 μm is achieved at the spindle speed of 2000 rpm, feed rate of 0.05 mm/tooth, and depth of cut of 2 mm.

Benchmarking has been widely recognized as an important tool of total quality management. Benchmarking has been also practised for a long time by different firms in different ways, such as in the implementation of technological systems like CAD/CAM, flexible manufacturing systems (FMS), and automobile manufacturing. AT&T and Xerox were some of the pioneer companies in benchmarking, they even developed their own benchmarking approaches. Benchmarking is a process of continuously measuring and comparing the company's performance level against the performance level of leading companies to determine the proper practices and actions that the company should implement to improve its performance. In this research, a generic framework for a metric that measures the overall effectiveness of the benchmarking process is laid out. In addition, a framework of a mathematical model for the optimal resource allocation of the benchmarking process is developed and its application is illustrated by an example. The above menti...

This paper establishes a vigorous methodology, based on the fuzzy set theory, to improve the facilities layout process that has occupied scholars and practitioners for more than four decades. Fuzzy set theory is an appropriate tool which uses the natural language that humans use to control complex systems such as facilities planning. The closeness rating between departments in a plant depends on qualitative and quantitative factors. Some of these factors may have greater effect on the designer's decisions about such ratings. Thus, the pairwise comparison of the analytical hierarchy process (AHP), which ensures the consistency of the designers’ decisions when assigning the importance of one factor over another, is used to find the weights of these factors. FUZZY, a computer program developed based on the fuzzy decision-making system (FDMS) is used to generate the activity relationship charts. These charts are used by FZYCRLP, a modified version of CORELAP, to develop the layouts. FELAP, another program bas...

Supplier selection is considered as an important factor for the success of any industry. The global competition and increasing growth of market demand increased the need for organisations to identify and select appropriate suppliers in order to fulfil customer demands on time with high quality and in cost effective manner. This paper will use quality function deployment (QFD) to translate the company stakeholder requirements into multiple evaluating factors for supplier selection and analytical hierarchal process (AHP) to determine the importance of evaluating factors and preference of each supplier with respect to each selection criterion such as delivery, price, quality and service. An integrated model, combining AHP and QFD is developed to select suppliers strategically. The proposed model is applied in automotive parts manufacturing company in Pakistan. Qualification and final selection of the suppliers for the considered real life case are based on the proposed methodology.

The fast development and use of IT and customer interactive websites has created great opportunities for enterprises involved in developing web application product in project-oriented environment. Many projects fail due to lack of clear identification of customer requirements, and lack of control of defects, especially when the defects have different weights according to their severity (effects) on the acceptance of the products. In this paper, we will firstly classify the severity of defects, secondly define the sign-off criteria for web-based application, and finally, determine whether the process is in statistical control using the demerits chart (U-chart), process capability analysis and fish bone diagram.

Outsourcing is a strategic decision that hotels need to take in order to reduce operating costs and improve competitiveness, but it remains important for them to scientifically select the appropriate outsourcing strategies. The aim of the study is to propose an integrated fuzzy multi-criteria decision making approach to come up with best outsourcing strategies. This approach evaluates the importance of various factors which motivates hotels to go for outsourcing services. In the present study a combination of fuzzy AHP and fuzzy TOPSIS is used to build up an approach that results in finding out weights to different motivating factors for outsourcing using fuzzy AHP. This is further extended with fuzzy TOPSIS to rank different services that can be outsourced and thus prioritising them.

This study describes a fuzzy-logic-based multiple-criteria decision-making approach to rank coals for industrial use. Calorific value and chemical compositions (i.e. sulphur, fixed carbon, volatile matter, moisture and ash contents) of coals are considered criteria. The desired values of each criterion are expressed by an appropriate fuzzy number, whereas all possible values of a criterion of a given coal are captured by a numerical range. A mathematical entity called ‘range compliance’ is used to formally compute the compliance between a given range (i.e. all possible values of a criterion of a given coal) and desired values of a criterion (i.e. a fuzzy number). The max-min operation is used to aggregate the contributions of all criteria to a single score so that the final decision is made based on crisp numerical values. A computerised decision-making tool called CoalExpert is developed to automate the coal ranking process.

Ceramics industry is an integral part of any country’s economic growth. Because of its competitive nature and wide range availability of ceramics, for both industrial and domestic consumers, it is important to have consistency in the quality of ceramics tiles. There are many defects identified in ceramics such as flatness, cracks, orthogonality, wrinkles etc. In this paper, many factors were identified during the firing process of production, which results in the convexity defect in tiles. A full factorial experiment that requires a total of 23 experimental runs (treatment combinations) for a complete replicate was carried out to determine the factors that affect the convexity occurrence. Minitab software was used to carry out regression analysis, analysis of variance, and residual analysis. The results show that the main factors below roll and above roll temperatures along with their respective interactions with the direct air blowing significantly affect the convexity of the tiles. Model implementation shows 41% reduction in convexity defects.

Material selection is a rapidly growing multi-criteria decision-making (MCDM) problem owing to the large number of factors affecting decision making. The right choice of available material is critical to the success and competitiveness of the manufacturing organisation. The analytical hierarchy process (AHP) is a tool designed to solve MCDM problems. The AHP was applied to select a material for a simple product (a key) utilising Expert Choice™ software. Confidence in the output is found to be high owing to the low inconsistency of the decision maker's judgement. Sensitivity analysis was performed to increase the confidence in the choice of material.

The purpose of this paper is to describe the experience and lessons learned from implementing the cooperative education option in the department of Industrial Engineering and Management at the University of Sharjah, UAE. The objectives are to analyze the impact of the cooperative training on the performance of the students and study the role of the co-op training in enhancing the achievement of student learning outcomes. The study confirms earlier results from prior studies which show, for example, that students who choose the co-op option have higher cumulative grade point average and show better achievement of program outcomes.