A three-stage model for closed-loop supply chain configuration under uncertainty

In this paper, a general closed-loop supply chain (CLSC) network is configured which consists of multiple customers, parts, products, suppliers, remanufacturing subcontractors, and refurbishing sites. We propose a three-stage model including evaluation, network configuration, and selection and order allocation. In the first stage, suppliers, remanufacturing subcontractors, and refurbishing sites are evaluated based on a new quality function deployment (QFD) model. The proposed QFD model determines the relationship between customer requirements, part requirements, and process requirements. In addition, the fuzzy sets theory is utilised to overcome the uncertainty in the decision-making process. In the second stage, the closed-loop supply chain network is configured by a stochastic mixed-integer nonlinear programming model. It is supposed that demand is an uncertain parameter. Finally in the third stage, suppliers, remanufacturing subcontractors, and refurbishing sites are selected and order allocation is determined. To this end, a multi-objective mixed-integer linear programming model is presented. An illustrative example is conducted to show the process. The main novel innovation of the proposed model is to consider the CLSC network configuration and selection process simultaneously, under uncertain demand and in an uncertain decision-making environment.     

A shieldless method for cryogenic cold–vapor supply usage: Theory and practice

We have proven by numerical analysis and experiment that with the use of the SRDB developed shieldless method for cryogenic vapor usage maximum vapor–cold usage is achieved. It is shown that evaporation is decreased in cryovessels and cryostats by using this method equal to 45 times for helium, 5 times for hydrogen and 1.7 times for nitrogen.     

Production and delivery policies for enhanced supply chain partnerships

Recent research on supply chain management has highlighted the importance of building strong customer–supplier relationships in order to gain competitive advantage. This paper examines the benefits of buyer–supplier partnerships over lot-for-lot, i.e. single setup single delivery (SSSD) systems and suggests two policies that the supplier can pursue in order to meet customers’ needs: (1) Single setup multiple delivery (SSMD), and (2) Multiple setup multiple delivery (MSMD). If its fixed setup cost is relatively high, the supplier would prefer to implement SSMD and produce an entire order with one setup. However, if the supplier can reduce the setup cost and the supplier's capacity is greater than the threshold level (P?=?2D), it is more beneficial for the supplier to implement the multiple setups and multiple deliveries (MSMD) policy, even though he pays more frequent setup costs since the savings in inventory holding costs is greater than the increased setup costs. In the latter case, setup reduction is realized by the knowledge and efficiency gained through frequent setup operations. To provide guidelines for the policy selection, we examine the interactions among variables, such as production capacity, learning rate, and holding costs for both parties. The paper also discusses the benefit sharing plan, which discusses according to the contribution (or sacrifice) each party made to the partnership efforts.     

RMS capacity utilisation: product family and supply chain

The paper contributes to development of RMS through linkage with external stakeholders such as customers and suppliers of parts/raw materials to handle demand fluctuations that necessitate information sharing across the supply chain tiers. RMS is developed as an integrated supply chain hub for adjusting production capacity using a hybrid methodology of decision trees and Markov analysis. The proposed Markov Chain model contributes to evaluate and monitor system reconfigurations required due to changes of product families with consideration of the product life cycles. The simulation findings indicate that system productivity and financial performance in terms of the profit contribution of product-process allocation will vary over configuration stages. The capacity of an RMS with limited product families and/or limited model variants becomes gradually inoperative whilst approaching upcoming configuration stages due to the end of product life cycles. As a result, reconfiguration preparation is suggested quite before ending life cycle of an existing product in process, for switching from a product family to a new/another product family in the production range, subject to its present demand. The proposed model is illustrated through a simplified case study with given product families and transition probabilities.     

Cooperative advertising in a supply chain with retail competition

This research assesses the effects of cooperative (coop) advertising in a channel with competing retailers considering both advertising and pricing as decision variables. We develop a game-theoretic model and provide equilibrium solutions for two games. In Game 1, the manufacturer and the retailers do not use cooperative advertising (status quo); and in Game 2, coop advertising is implemented. We also obtain optimal solutions for the case where the channel is coordinated. Contrary to the results provided for one-manufacturer, one-retailer channels, we find that coop advertising may not be profitable for the retailers or for the channel, especially when the market is characterised by low levels of price competition and high advertising competition between retailers. Although it benefits the manufacturer, the total effect of cooperative advertising on the channel profit might be negative under such conditions. The results also show that coop advertising stimulates retailers’ spending but may result in lower advertising expenditures than for a fully coordinated channel. Finally, when coop advertising benefits the entire channel, it does not fully achieve results from vertical integration.     

Ontology-based interoperability solutions for textile supply chain

Existence of interoperability within the enterprises is essential for textile supply chain to efficiently face the challenges from contemporary competitors,to find new business opportunities and to render better customer service.Exchange of business documents,being semantically consistent,is the way to achieve interoperability.However,heterogeneity of the structures of the enterprises poses challenges for establishing interoperability.Ontology based semantic interoperability framework has now been proven as an effective solution for enterprise interoperability.In this paper,the existing ontology-based interoperability solutions in the context of textile supply chain have been compiled and research gaps have been identified.The ontological methods,such as unified process for ontology(UPON) and methontology have been analyzed,and UPON have been shown as a suitable ontology development method for textile supply chain.     

Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation

This paper describes a relational database system for semi-generative process planning for sheet metal parts that emulates expert system capabilities. The system integrates a feature-based relational database for the parts, a forward chaining rule-based strategy for machine selection, both global and feature-specific execution of the rules and a graph theoretic cost optimization model for optimal process plan selection. This system, which is currently being developed for a sheet metal fabrication company, suggests that, using the experience of shopfloor personnel, an efficient integration of feature-based process planning and expert system strategies can be accomplished.     

Role of corporate memory in the global supply chain environment

Critical knowledge is proliferated among different knowledge owners of a corporate system through the individuals lying inside or outside the system. Extraction of such knowledge is a very crucial requirement for all organisations. This paper presents the role of critical knowledge in the proper functioning of a system by representing it in the form of eXtensible Markup Language to develop a corporate memory. In order to demonstrate the role of corporate memory in the organisation, a real-world problem of a global supply chain is considered. The problem utilises the concept of corporate memory for the selection of potential suppliers from a set of available suppliers, and further to select the best route from a set of available alternative routes. The objective deals with the minimisation of logistic cost. A fuzzy-based decision-making approach together with the genetic-algorithm-based solution methodology was applied to solve the underlying problem on a set of randomly generated data sets. A comparison between two cases, i.e. the problem with the presence of corporate memory and the problem without corporate memory, was performed. The results obtained reveal the importance of corporate memory in optimising the underlying task (i.e. minimisation of logistic cost). Further, a sensitivity analysis was performed on the various transportation routes to check the deviation in the objective value by varying the problem parameters.     

Fundamental performance of novel power supply for HTS magnet using solar energy system

A technical fusion is an important option to establish renewal development in the mutual fields. We have proposed a novel superconducting power supply that is combined with superconducting power supply and solar energy system. An eternal electric energy can be converted by solar energy system, which contains solar panel, photovoltaic (PV) controller and energy-storing battery, can be utilized in the utility power of superconducting power applications. The novel power supply could operate without external utility power to charge the HTS load magnet due to the solar energy. We can improve the operating efficiency and install it in remote locations where utility power is not available. In this paper, as a first step of this work, we showed the possibility of technical fusion between a superconducting power supply and a solar energy system.     

From Studio to Street: The Urban Photography of Man Ray

Dada and Surrealist photographer Man Ray is rarely associated with street photography, a genre popular with artists and writers of the 1920s and 1930s. Yet his work demonstrates a closer connection to this area than has previously been acknowledged. From the early Dada constructions to the later photographic depictions of Paris and New York, the city played a crucial role in Man Ray's artistic output. This essay explores Man Ray's urban photography not as an uncharacteristic shift of concerns, as some critics have argued, but rather as an extension of the aesthetic approach taken in his more famous studio-based works. It explores the influence of Eugène Atget, whom Man Ray claimed to have ‘discovered’, and argues that the latter draws on the older photographer's compositional structures, pushing them into more abstract, formalist territory.     

New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management

Greening the supply chain is an increasingly important concern for many business enterprises and a challenge for logistics management. Critical functions within green supply chain management are internal improvements and selection of green suppliers. This study proposes a novel, hybrid model that addresses dependent relationships between various criteria and the vague information coming from decision-makers. The Decision-making Trial and Evaluation Laboratory (DEMATEL) technique structures the relationships among criteria, thereby constructing an influential network relationship map (INRM). Meanwhile the DEMATEL-based, analytical network process (ANP) method aids in obtaining influential weights of the criteria. Decision-makers may hold diverse opinions and preferences due to incomplete information, differences in knowledge or simply conflicts that are inherent between various departments. This can make it difficult to judge the performance of alternatives. One remedy is to apply a modified COmplex PRoportional ASsessment of alternatives with Grey relations. Next, this is applied to improve each criterion for integration of the performance values obtained in closing the aspiration level from different expert opinions based on INRM. An empirical example using data from a Taiwanese electronics company is provided to demonstrate our proposed method. The results can provide firms with a knowledge-based understanding of the source of some problems, thus reducing the performance gaps and closing the aspiration levels. Finally, there is a discussion on certain managerial implications.     

Evaluating the effects of capacity constraints and demand patterns on supply chain replenishment strategies

This research considers inventory replenishment in a stochastic, multi-echelon supply chain involving both production and distribution functions. Simulation is used to compare distribution/material requirements planning (DRP/MRP), re-order point (ROP) and Kanban (KBN) replenishment strategies. Additional experimental factors include the demand pattern and the existence of manufacturing capacity constraints. Trade-off curves between inventory and delivery performance are generated. Statistical techniques, including analysis of variance (ANOVA), are then used to compare the areas under the trade-off curves and determine the relative dominance among the replenishment strategies. The methodology is used to identify both main and interaction effects. With seasonal demand, DRP/MRP performance is found to be best, followed by ROP and KBN, respectively. Without seasonal demand, the relative performance ranking depends on the presence of capacity constraints. Without capacity constraints, ROP performs best, followed by DRP/MRP and KBN. With capacity constraints, the ranking is reversed. This difference in behaviour can be explained using queuing analysis.     

Integrated model for the batch sequencing problem in a multi-stage supply chain: an artificial immune system based approach

In this paper a mathematical model for the batch sequencing problem in a multistage supply chain is developed by taking into account three practically important objectives, viz. minimization of lead time, blocking time and due date violation. Attribute dependent operation time, sequence dependent setup time, different due dates, different lot sizes for batches and variable time losses due to interaction among several stages like waiting, idling, and blocking are also considered in the model. The problem is combinatorial in nature and complete enumeration of all its possibilities is computationally prohibitive. Therefore, a metaheuristic, artificial immune system (AIS) is employed to find an optimal/near optimal solution. In order to test the efficacy of AIS in solving the problem, its implementation on four different problems has been studied. Further, the comparative analysis of the results obtained by implementing AIS, genetic algorithm (GA) and simulated annealing (SA) on the proposed model reveals that AIS outperforms GA and SA in solving the underlying problem.     

Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g. food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualisation of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.     

A goal programming model for the operation of closed-loop supply chains

The implementation of closed-loop supply chains to handle the problem of increasing levels of electronic and electrical equipment waste can be beneficial both economically and ecologically. Three different problem analysis techniques—why–what's stopping analysis, fundamental objective hierarchy, and means objective network—are used to analyse the problem from various perspectives. A non-preemptive goal-programming model and solution approach have also been developed, with goals being assigned different weights according to the respective goal priorities. The model considers multiple products, as well as operations associated with the product, subassembly, part, and material levels. A major contribution of the research involves the fact that the objectives and related constraints for each member of the supply chain are explicitly modeled. The results of the analysis show both the effect of varying the priority/weight associated with a goal, and how the values of the deviational variables can aid a decision maker in model analysis.     

A multi-objective and integrated model for supply chain scheduling optimization in a multi-site manufacturing system

In a supply chain, scheduling plays a significant role in coordinating and cooperation. This article considers an integration of supplier and vehicle scheduling problems in terms of vehicle routing determination for transporting raw materials from the suppliers to some manufacturing centres. The aim is to minimize the total tardiness of all assigned orders to the suppliers and simultaneously minimize the total travelled distance of the vehicles. Most manufacturing companies, which have to manage their suppliers as an industrial unit, experience this problem. A new metaheuristic algorithm called the multiple league championship algorithm (MLCA), inspired by championship matches, is proposed to solve this problem. To show the efficiency of MLCA, it is compared with two different algorithms used for the problems in the literature that are closest to this problem and a soccer-based algorithm called golden ball. The experimental results prove that the proposed algorithm has better performance than these algorithms.