Unveiling the relation between the challenges and benefits of Operational Excellence and Industry 4.0: A Hybrid Fuzzy Decision-Making Approach

Operational excellence (OpEx) is a direction toward learning and developing an excellent culture in all aspects of an organization. To reach this culture, revolutionizing activities using industry 4.0 (i4.0) technologies might be a significant empowering tool. This study aims to identify the challenges and benefits of both concepts and investigate their interrelationship to be considered in applying industry 4.0 technologies toward operational excellence. The challenges and benefits of OpEx and i4.0 are identified and finalized by reviewing the literature. The causal relations between the considered factors are extracted using the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) method. Then, the analytical network process (ANP) is applied to determine the importance and weight of the factors (challenges and benefits of OpEx and i4.0) according to the constructed network. The findings illustrated a strong network structure between the factors. First, the causal factors included OpEx and i4.0 challenges, while the OpEx challenges also affected the i4.0 challenges. Both group challenges had a significant effect on OpEx and i4.0 benefits. This means that challenges are the causal factors to be considered in the alignment of i4.0 toward OpEx. Among the OpEx challenges, lack of strategic planning and proper infrastructure were the main influential factors. In contrast, lack of government support and undeveloped business models were identified as the main challenges of i4.0. OpEx and i4.0 concepts are reviewed, and their pros and cons are studied. Previous studies determined an interaction among these concepts. However, from a practical viewpoint, the relation between the challenges and benefits of i4.0 and OpEx was studied for the first time for their alignment

Investigating Potential Interventions on disruptive impacts of Industry 4.0 technologies in Circular Supply chains: Evidence from SMEs of an Emerging Economy

As a transversal theme, the intertwining of digitalization and sustainability has crossed all Supply Chains (SCs) levels dealing with widespread environmental and societal concerns. This paper investigates the potential interventions and disruptive impacts that Industry 4.0 technologies may have on pharmaceutical Circular SCs (CSCs). To accomplish this, a novel method involving a literature review and Pythagorean fuzzy-Delphi has initially been employed to identify and screen categorized lists of Industry 4.0 Disruptive Technologies (IDTs) and their impacts on pharmaceutical CSC. Subsequently, the weight of finalized impacts and the performance score of finalized IDTs have simultaneously been measured via a novel version of Pythagorean fuzzy SECA (Simultaneously Evaluation of Criteria and Alternatives). Then, the priority of each intervention for disruptive impacts of Industry 4.0 has been determined via the Hanlon method. This is one of the first papers to provide in-depth insights into advancing the study of the disruptive action of Industry 4.0 technologies cross-fertilizing CE throughout pharmaceutical SCs in the emerging economy of Iran. The results indicate that digital technologies such as Big Data Analytics, Global Positioning Systems, Enterprise Resource Planning, and Digital Platforms are quite available in the Irans' pharmaceutical industry. These technologies, along with four available interventions, e.g., environmental regulations, subsidy, fine, and reward, would facilitate moving towards a lean, agile, resilient, and sustainable supply chain through the efficient utilization of resources, optimized waste management, and substituting the human workforce by machines

An Integer Grey Goal Programming For Project Time, Cost and Quality Trade-Off

Project management (PM) is one of the prominent fields in business and industry. Every task of an organization can be imagined as a project, being a coordinated set of activities toward a common goal. One important aspect of PM is analysing the information related to the optimum balance among the project’s objectives. Each project is a combination of different activities, being connected to each other and having several success criteria, among which the time, cost and quality of the project completion are more significant, due to their significant effect on obtained results. Accordingly, the time might lead to delay and penalty which means more cost; and cost may be underestimated than real required funds. They both will lead to failure in project management. On the other hand, quality is the final key which confirms the success. The aim of a time-cost-quality trade-off problem (TCQTP) is to select a set of activities and an appropriate execution mode for each activity; the cost and time of the project is minimized while the project quality is maximized. The purpose of this paper is to present a model for TCQTP in which these parameters are approximated by grey numbers. Since there are various modes to accomplish each activity, the trade-off problem is formulated based upon a multi-objective integer grey programming model. Afterwards, a goal programming- based approach is designed to solve this model. The model's results provide a framework for the project manager to manage his/ her project successfully, in acceptable time, with the lowest cost and the highest quality. The main originality of the proposed model is the approximation of time, cost and quality parameters of activities mode with grey numbers and the development of a two phase goal programming- based approach to solve this problem. Ultimately, the proposed model is applied in two different cases and results are illustrated to clarify the outstanding capabilities of the mode

A bi-objective score-variance based linear assignment method for group decision making with hesitant fuzzy linguistic term sets

open access articleDecision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method

A Novel Location-Inventory-Routing Problem in a Two-Stage Red Meat Supply Chain with Logistic Decisions: Evidence from an Emerging

This study focuses on a specific method of meat production that involves carcass purchase and meat production by packing facilities with a novel two-stage model that simultaneously considers location-routing and inventory-production operating decisions. The considered problem aims to reduce variable and fixed transportation and production costs, inventory holding cost and the cost of opening cold storage facilities. The proposed model encompasses a two-stage model consisting of a single-echelon and a three-echelon many-to-many network with deterministic demand. The proposed model is a mixed-integer linear programming (MILP) model which was tested with the general algebraic modelling system (GAMS) software for a real-world case study in Iran. A sensitivity analysis was performed to examine the effect of retailers' holding capacity and supply capacity at carcass suppliers. In this research, the number of products transferred at each level, the number of products held, the quantity of red meat produced, the required cold storage facilities and the required vehicles were optimally specified. The outcomes indicated a two percent (2%) decrease in cost per kg of red meat. Eventually, the outcomes of the first and second sensitivity analysis indicated that reduced retailers' holding capacity and supply capacity at carcass suppliers leads to higher total costs. This research proposes a novel multi-period location-inventory-routing problem for the red meat supply chain in an emerging economy with a heterogeneous vehicle fleet and logistics decisions. The proposed model is presented in two stages and four-echelon including carcass suppliers, packing facilities, cold storage facilities and retailers.N/

Dynamic Prioritization of Equipment and Critical Failure Modes: An Interval-Valued Intuitionistic Fuzzy Condition-Based Model

The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW). To realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated. To prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results. In this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu

Coordination in a Closed-Loop Sustainable Supply Chain Considering Dual-Channel and Cost-Sharing Contract: Evidence from an Emerging Economy

Due to the significant role of the reverse supply chain (RSCs) in collecting used products and achieving a sustainable environment, both scholars and industries have paid close attention to pricing in reverse and closed-loop supply chains (CLSCs). Moreover, with the rapid development of the internet and e-commerce in the latest decades, researchers have examined the impact of constructing online return channels based on customer behavior. In this article, a game-theoretic approach was applied to find the optimal economic and environmentally sustainable solutions in a two-level CLSC with a dual collecting channel including the retailer’s traditional channel and the manufacturer’s online channel. The purpose of the current study is to optimise the selling price, acquisition prices, market demand, channels return rate, the portion of manufacturing new products, and cost-sharing contract (CSC) participation shares for each player. For this purpose, various policies, such as centralised and decentralised modes, different structures such as Nash bargaining power, manufacturer-leader Stackelberg, and retailer-leader Stackelberg have been considered. However, the main contribution of this work compared to the existing literature is considering two CSCs from both retailer and manufacturer points of view, with a real case analysis from an emerging economy. In addition, a comprehensive sensitivity analysis has been carried out to enhance the validation of the proposed model. The results indicated that the manufacturer-leader Stackelberg strategy leads to the lowest profit for the SC in both decentralised and cooperative policies. However, when the retailer and manufacturer have equal decision-making power (Nash strategy) and the retailer participates in the remanufacturing cost (i.e. cost-sharing type-2) both the economic and environmentally sustainable goals of CLSC were met

Unveiling the Role of Sustainable Supply Chain Drivers Toward Knowledge-Based Economy via a Novel Permutation Approach: Implications from an Emerging Economy

Knowledge-based supply chains (KBSC) focus on cutting-edge technologies of industry 4.0 and are highly focused on knowledge and human-centric skills. On this account, their prominent role in the context of knowledge economies is undoubtedly confirmed. On the other hand, many scholars and activists have considered the sustainability triple bottom line (TBL) theory as the fundamental pillar of development, including the economy, environment, and society. As a result, the main purpose of this study is to demonstrate the role of sustainable supply chain drivers (SSCDs) in achieving a knowledge-based economy. To this aim, after extraction of the main features of the knowledge-based economy (KBE) and sustainable supply chain drivers from relevant literature, a new method based on an efficient mixed-integer linear programming (MILP) model is developed to relax the computational complexity of the classical QUALIFLEX (QUALItative FLEXible multiple criteria method) in dealing with the problem with more alternatives. The results presented that among identified features of KBE, the literacy rate, life-long training, learning, and technical publications per capita are essential features. Furthermore, long-term orientation, globalization process, and professional associations are the most crucial supply chain sustainability drivers. These findings can empower organizations to prepare for moving toward sustainability in a knowledge-based economy environment

Measuring staff satisfaction in transportation system using AHP method under uncertainty

One of the most important challenges in today world is the transportation and satisfaction of this system. Measuring satisfaction in transportation has been done quantitatively so far and, more importantly, the measurement process has not usually been scientific. This study aimed at an accurate scientific measurement. Because of ambiguity, this paper discusses how to use the intuitionistic fuzzy method, in which both membership and non-membership functions were expressed. Therefore, initially, considering the results of previous researches, as well as studying the references and standards, the characteristics and basic criteria, a researcher-made questionnaire with a reliability of 0.95 was first performed and then the weights were determined using the AHP intuitionistic fuzzy method. After performing the above steps, the intuitionistic fuzzy satisfaction value was calculated at different levels and using the method, the final number of satisfaction was defuzzified