Modeling enablers of supply chain risk mitigation in electronic supply chains: A Grey–DEMATEL approach

Supply chains are becoming perpetually complex and potentially vulnerable due to increased globalization and vertical integration. Supply chain managers are conscious that the success of any supply chain lies in its proficiency to manage risks efficiently and effectively. Supply chain risk management (SCRM) signifies proactive practices of managing vulnerability of supply chains. Various firms espouse strategic level measures for risk mitigation and implement practices for enhancing supply chain resilience. In order to enhance supply chain resilience, the enablers of supply chain risk mitigation need to be acknowledged and implemented into practice. This research emphasizes on ascertaining the major enablers of supply chain risk mitigation with emblematic focus on electronic supply chains. A blend of Grey theory and DEMATEL approaches has been employed in this research to find out cause/effect relationships among the enablers of supply chain risk mitigation. This exercise helps to find which can be the driver to initiate the effects of other driven enablers. Sensitivity analysis was also conducted of the results to ensure reliability of solutions. The results show that that the enablers of supply chain risk mitigation are intertwined and one enabler can be the cause/effect of one or more enablers of supply chain risk mitigation. Dynamic assortment planning is found to be the decisive causal enabler, as it initiates the effects of many other enablers of supply chain risk mitigation, followed by accurate demand forecasting and flexible supply contracts. Cause–effect relationships plotted facilitate managers to ascertain primary causal enablers that need imperative attention in dealing with vulnerability issues of supply chain. Managers can take proactive steps to address and implement primary causal enables of risk mitigation into practice for reducing total risk impacts of the supply chain.     

Supply chain ontology: Review, analysis and synthesis

In an environment where supply chains compete against supply chains, information sharing among supply chain partners using information systems is a competitive tool. Supply chain ontology has been proposed as an important medium for attaining information systems interoperability. Ontology has its origin in philosophy, and the computing community has adopted ontology in its language. This paper presents a study of state of the art research in supply chain ontology and identifies the outstanding research gaps. Six supply chain ontology models were identified from a systematic review of literature. A seven point comparison framework was developed to consider the underlying concepts as well as application of the ontology models. The comparison results were then synthesised into nine gaps to inform future supply chain ontology research. This work is a rigorous and systematic attempt to identify and synthesise the research in supply chain ontology.     

Performance of supply chain collaboration – A simulation study

In the past few decades several supply chain management initiatives such as Vendor Managed Inventory, Continuous Replenishment and Collaborative Planning Forecasting and Replenishment (CPFR) have been proposed in literature to improve the performance of supply chains. But, identifying the benefits of collaboration is still a big challenge for many supply chains. Confusion around the optimum number of partners, investment in collaboration and duration of partnership are some of the barriers of healthy collaborative arrangements. To evolve competitive supply chain collaboration (SCC), all SC processes need to be assessed from time to time for evaluating the performance. In a growing field, performance measurement is highly indispensable in order to make continuous improvement; in a new field, it is equally important to check the performance to test conduciveness of SCC. In this research, collaborative performance measurement will act as a testing tool to identify conducive environment to collaborate, by the way of pinpointing areas requiring improvements before initializing collaboration. We use actual industrial data and simulation to help managerial decision-making on the number of collaborating partners, the level of investments and the involvement in supply chain processes. This approach will help the supply chains to obtain maximum benefit of collaborative relationships. The use of simulation for understanding the performance of SCC is relatively a new approach and this can be used by companies that are interested in collaboration without having to invest a huge sum of money in establishing the actual collaboration.     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

Supporting agile supply chains using a service-oriented shop floor

The globalized nature of current business environments led to the emergence of new networked enterprise organizational paradigms (supply chains, extended enterprises, virtual enterprises, collaborative networks, etc.) to meet changing requirements and tackle profitable but volatile opportunities overall agility is required.Eventually the shop floor will have to react and accommodate (re)adjustments in the supply chain making it an important piece in the competitiveness puzzle. So far, the research focus has been in high level aspects of supply chain management and the integration of shop floor activities in the process has been left relatively unattended.However, shop floor data is increasingly required in business tools that support decision making. In this context, failing to support agility at shop floor level can compromise the agility of the supply chain.Recent developments in networked information technologies and embedded devices allow enabling intelligence in shop floor rendering it an active and live entity that further enhances the dynamics of the supply chain.The goal of the present work, supported by an implemented test case in the assembly domain, is to demonstrate how one is able to seamless integrate the shop floor with external tools and achieve a highly reconfigurable environment that adapts to changing production requirements and disturbances using service-oriented technology.     

Design of agile supply chain assessment model and its case study in an Indian automotive components manufacturing organization

Agile Manufacturing (AM) paradigm is fast instilled in modern organizations. AM enables an organization to evolve products and services quickly and economically in response to the customers’ dynamic demands. The effectiveness of AM is largely determined by the performance of Agile Supply Chains (ASC). In order to assess their performance, an ASC assessment model was reported in this research paper. This model is encompassed with agile supply chain attributes whose performance levels need to be determined for assessing the overall ASC performance of the organization. The computation was performed using fuzzy logic approach. The working of this model was examined by conducting a case study in an Indian automotive components manufacturing organization. The experience gained by conducting this case study favored the use of a computerized system which will ensure accuracy of computations involving fuzzy logic.     

A game-based approach towards facilitating decision making for perishable products: An example of blood supply chain

Supply chains for perishable items consist of products with a fixed shelf life and limited production/collection; managing them requires competent decision-making. With the objective of placing the learners in the position of decision-makers, we propose the Blood Supply Chain Game which simulates the supply chain of blood units from donors to patients based on a real case study modeling the UK blood supply chain. The Excel-based game is an abstraction of the technical complex simulation model providing a more appropriate learning environment. This paper presents the game’s background, its mathematical formulations, example teaching scenarios and the learners’ evaluation. The game aims to translate qualitative aspects of a sensitive supply chain into quantitative economic consequences by presenting a process analysis and suggesting solutions for the patient’s benefit in a cost effective manner, trying to synchronize blood demand and supply and maximize the value of the whole supply chain. This innovative approach will be instructive for students and healthcare service professionals.     

考虑产品替代的供应链协调问题研究

替代品大大增加了企业间的竞争,使企业难以达到所期望的盈利水平。对供应链进行合理有效的管理可最大限度地促进企业适应当今多变的市场环境。人们对于产品的需求不仅仅取决于产品本身的价格,也取决于互补产品的价格。对此,构建一个以产品替代的供应链协调问题为研究目标,以两种供应链管理模式(集中供应链(CSC)和分散供应链(DSC))为依托,通过建立混合整数规划模型并对相关参数进行验证,得出集中供应链模式更能灵活应对当今市场。     

Review of supply chain performance measurement systems: 1998–2015

In today’s competitive business environment, supply chain performance is one of the most critical issues in various industries. It is argued that supply chain performance measurement is fundamental to efficient supply chain management. Over the past two decades, several frameworks and systems have been developed to meet this need. This study reviews the literature in the field of supply chain performance measurement and assembles an overview of those systems, approaches, techniques and criteria. For this purpose, 83 of 374 related articles from 1998 to 2015 were selected for final review using the Scopus and ISI databases. Findings disclose that performance measurement in supply chain contexts is still a fruitful area of research. The study also provides an overview of the performance measures employed in supply chain systems. These findings present a solid basis for future academic and practitioner work in the field of supply chain performance measurement.     

Optimizing supply chain network for perishable products using improved bacteria foraging algorithm

In a supply chain environment, time delay has a significant impact on the success of perishable products. A major concern is therefore aimed at development of a holistic optimized approach in a supply chain environment for perishable products. Thus, integration of production, inventory and, distribution of perishable products in a supply chain environment are the challenging tasks for practitioners and researchers. In general, the standard optimal supply chain model cannot work for perishable products. There is therefore, a need for a holistic model that focuses on the consolidation of the processes. Shorter product shelf-life, temperature control, requirement of strict tractability, large number of product variants, and a large volume of goods handled are the major challenges in a supply chain environment for perishable products. The present work focuses on the development of a holistic model which uses improved bacteria forging algorithm (IBFA) for solving the formulated model. We have proposed and analyzed some general properties of the model and, finally applied it to a three-stage supply chain problem using an IBFA. Two case studies have been considered for support and demonstration of the integrated perishable supply chain network problem. Results obtained from IBFA reveal that the proposed model is more useful for decision makers while considering optimal supply chain network for perishable products. Finally, validation of results has been carried out using bacteria forging algorithm (BFA). The computational performance of the proposed algorithm proves that IBFA is instrumental in effectively handling the proposed approach.     

System dynamics of supply chain network organization structure

Information technology is providing manufacturers with additional flexibility with regard to their supply chain network choices. Our research studies supply chain network organization structures categorized by the organic and mechanistic management control structures. The structural impacts on cost and fill rate performance are studied in two-echelon and two-supply-chain network organization models under different market coordination conditions using system dynamic simulations. Our results show significant effects of demand and network structural factors, and their interactions, on these measures. As demand becomes dynamic, the cooperative interaction model, where supply chains cooperate to satisfy customer demand, is found to have better system performance than the competitive supply chain model. The analysis also suggests that increasing the responsiveness at the downstream plant is particularly important to the overall system performance improvement.     

Supply chain redesign for resilience using simulation

Supply chains are facing numerous changes that are contributing to increasing their complexity and vulnerability to disturbances, therefore, to survive, supply chains must be resilient. The paper presents a supply chain simulation study for a real case concerned with the Portuguese automotive supply chain. The subset automotive supply chain involved in the case study is a three-echelon supply chain, composed by one automaker, two 1st-tier suppliers, two 2nd-tier suppliers, and one outsource entity. The purpose of the study is to evaluate alternative supply chain scenarios for improving supply chain resilience to a disturbance and understanding how mitigation strategies affect each supply chain entity performance. Two strategies widely used to mitigate disturbance negative effects on supply chains were considered and six scenarios were designed. The scenarios differ in terms of presence or absence of a disturbance in one hand and presence or absence of a mitigation strategy in other hand. To evaluate the scenarios designed, two performance measures were defined per supply chain entity, Lead Time Ratio and Total Cost.     

Implementation of intelligent systems, enabling integration of SMEs to high-value supply chain networks

In the face of increasing competition from low-cost economies, European manufacturing companies are focusing on optimisation of operational activities to remain competitive. Previous work has identified how companies can optimise implementation of specialist technology to improve production capability; however increasing demands in service requirements such as customisability and flexibility are often negating the localised gains in capability.Supply chain management has become an increasingly important aspect of operations improvement to ensure support throughout the product realisation process. The key to creating a supply chain capable of this rapid response and high level of adaptability is integration of intelligent systems and management capabilities.A site-visit-based survey and characterisation of small and medium enterprises (SMEs), comprising actual or potential supply chain components, reveals that even those with well developed capabilities and attitudes to adopting production technologies are largely not proactive with technology adoption targeting these needs.A review of requirements for SMEs to achieve such competitive supply chain capabilities reveals a hierarchy of technical expertise to be developed. This is presented as an implementation strategy for staged introduction of these tools and techniques with a view to establishing high-value supply chains capable of withstanding business pressures from developing economies.     

A flexible agent system for change adaptation in supply chains

The importance of supply chain management is increasing with globalization and the advancement of electronic business. Supply chains are dynamic due to frequent changes in suppliers, customers, and products. However, information systems for supply chains are not flexible enough to adapt to the changes, requiring high cost and time for re-implementation and re-customization. This paper suggests a flexible agent system for supply chains that can adapt to the changes in transactions introduced by new products or new trading partners. The flexible agent system consists of an interpretable conversation policy model, a procedure for exchanging new conversation policies, and a mechanism for actual transactions with newly acquired conversation policies. By using the flexible agent system, formation of supply chains becomes more robust to the dynamic changes. To show how the approach can be realized, a PC supply chain application is illustrated with a prototype agent platform.     

Simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management

One of the most critical issues facing supply chain managers in today’s globalized and highly-uncertain business environment is how to proactively deal with risks that might cause serious severances and distortions of material flows in a supply chain. This paper proposes a simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management, which proactively deals with the negative consequences of random and hazardous risk events in sourcing, production, distribution, and transportation in an integrated way. The proposed approach incorporates the production lot size of the plant, order quantity and reorder point of DC, and five response coefficients as decision variables to potential risks. The proposed approach is successfully applied to an industrial example of a consumer electronics manufacturing company. The results of the computational study show that the systematic risk management of global supply chains using the proposed approach increases the profit by 20% and 16.1% in the industrial example in comparison with passive and active risk management, respectively. In addition, a mixed strategy for the inventory management of distribution centers is suggested to improve the profits of global supply chains subject to substantial risks.     

Supply chain positioning strategy integration, evaluation, simulation, and optimization

When a company faces the global market, they would have to reengineer their processes and reorient their operation strategies, such as supply chain positioning strategy (SCPS) to benefit the most from a given situation. SCPS refers to actions taken by firms to respond to and satisfy customers' demand. The traditional concepts of production positioning strategy has been extended in this paper to develop various supply chain positioning strategies with a view that, for different production strategies, supply chain strategies should also be different. Obviously, each typical strategy has its advantages and limitations, and only fits for some certain scenarios. In this study, typical SCPSs have been defined, analyzed and classified. Supply chain dynamics and their impact on various strategies are also discussed. Subsequently, general integration approaches of the proposed strategies have been explored. Then, an approach for implementing SCPS in electronics industry is elaborated. It is shown that with integrated strategies, companies can get their desired optimal business values, even under great supply chain dynamics. It is expected that this method would be suitable for global organizations that has a need to cater to varying demands in different regions.     

Introducing a mixed-integer non-linear fuzzy model for risk management in designing supply chain networks

Nowadays, supply chains play an inevitable role in prompt handling of varying customers’ needs. Administration of a successful supply chain depends on how efficiently the network design is accomplished. Therefore, a supply chain network design problem is considered in this paper. The network addresses an uncertain environment threatened by different risk sources in order to captivate the real world conditions. A mixed-integer non-linear mathematical model is developed in which the uncertainties are represented by the fuzzy set theory. Benders decomposition is then applied to solve the proposed problem; consequently, the model is transformed into a mixed-integer one. Moreover, an interactive resolution method is applied to provide the decision maker with alternative decision plans in regard to different satisfaction degrees. Finally, the accuracy of the proposed model is checked by sensitivity analysis test and its performance is considered by different numerical examples.     

On-demand e-supply chain integration: A multi-agent constraint-based approach

With e-business emerging as a key enabler to drive supply chains, the focus of supply chain management has been shifted from production efficiency to customer-driven and partnership synchronization approaches. This strategic shift depends on the match between the demands and offerings that deliver the services. To achieve this, we need to coordinate the flow of information among the services, and link their business processes under various constraints. Existing approaches to this problem have relied on complete information of services and resources, and have failed to adequately address the dynamics and uncertainties of the operating environments. The real-world situation is complicated as a result of undetermined requirements of services involved in the chain, unpredictable solutions contributed by service providers, and dynamic selection and aggregation of solutions to services. This paper examines an agent-mediated approach to on-demand e-business supply chain integration. Each agent works as a service broker, exploring individual service decisions as well as interacting with each other for achieving compatibility and coherence among the decisions of all services. Based on the framework, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach.     

A web-based approach for exceptions management in the supply chain

This research aims at developing collaborative planning and scheduling in complex and dynamic supply chains by providing a software architecture and a methodology to define cooperation in a distributed environment. The study contributes to gain the competitive advantage at the extended enterprise, since it analyzes the implications of changes occurred at a certain point of the supply chain for other nodes. This way, the different production schedules of the supply chain are coordinated in order to find a best global solution, thus leading to more realistic plans, better due date fulfilment and less inventory levels in the supply chain as a whole. The general framework of the project using a decentralized approach can be defined by means of three subsystems of communication based on agents: (i) a communication subsystem inside the plants, which will manage the unforeseen events that may lead to a rescheduling of part or the entire production plan, (ii) an inter-plants communication subsystem, which will manage the events produced in a plant that may affect other plants and (iii) a supply chain communication subsystem, which will manage events occurred in a plant that can affect suppliers and/or customers. Next steps will include full development and systematic tests of the prototype that will check the suitability of the architecture and algorithms selected. This research is being funded by Grant PI2008-08 from the Basque Government in Spain.     

A modified failure mode and effects analysis method for supplier selection problems in the supply chain risk environment: A case study

In the emerging supply chain environment, supply chain risk management plays a more important role than ever. Companies must focus not only on the efficiency of supply chain, but also on its risks. If an unanticipated event occurs, all of the supply chain members will be impacted, and the result will cause significant loss. Therefore, this research proposes a modified failure mode and effects analysis (MFMEA) method to select new suppliers from the supply chain risk’s perspective and applies the analytic hierarchy process (AHP) method to determine the weight of each criterion and sub-criterion for supplier selection. An IC assembly company is then studied to validate this model. The result shows that the case company can categorize its suppliers more effectively and at the same time select a low-risk supply chain partner. Moreover, the case company can provide unsatisfactory suppliers with valuable feedback that will help them improve and become its partners in the future.