Real-time Supply Chain Research Articles

Supply chain sustainability strategy selection using integrated multi-criteria decision-making method

In recent years, industries have begun taking up proactive leadership and working together with their supply chain partners to implement initiatives for improving the sustainability of the supply chain. Sustainability performance improvements in industries are essential for survival rather than meeting the regulatory and reporting requirements. This paper aims at determining the major sustainability criteria and prioritising the given sustainability strategy sets to achieve the highest sustainability performance. This multi-criteria decision-making (MCDM) problem is solved by the application of the analytic hierarchy process (AHP) and preference ranking organisation method for the enrichment of evaluations (PROMETHEE) techniques in an integrated way. In this study, criteria for comparing the alternatives are identified from literature. The criteria weights are obtained using AHP methodology and are used in the PROMETHEE (I and II) for ranking the strategy sets. The proposed methodology is applied to solve a real-time supply chain decision-making issue of an Indian manufacturing industry. The most sustainable strategy proposal is identified. Sensitivity analysis is carried out on the variations in ranks with respect to the deviation in criteria weights. The minimum deviations in criteria weights that cause rank reversal are also identified from this. It facilitates getting insights into the stability of the ranks to the decision maker.

A supply chain performance measurement approach using the internet of things

PurposeThe purpose of this paper is to introduce a more practical approach for supply chain performance measurement (SCPM) and to approve the promising role of internet of things (IoT) technologies in SCPM systems.Design/methodology/approachThis is a conceptual paper that includes literature review analysis, designing a new approach for SCPM, and a case study scenario for proving its applicability.FindingsThe case study scenario shows that IoT can enhance SCPM, as it has the capability to enable real-time data collection, increase data efficiency as long as enable real-time communication within the supply chain (SC).Practical implicationsThe proposed approach can help to develop performance measurement systems and applications enabled by IoT technologies. These systems can be used to monitor, manage, and control the overall SC in real time and in a more integrated and cooperative manner.Originality/valueThis paper provides a structured systems building approach tailored to show how to employ IoT technologies in the field of SCPM. This approach could help in establishing new performance measurement applications, and it is believed that both practitioners and researchers will benefit from it.

The risk control evaluation for supply chain based on knowledge management

The supply chain risk control has recently attracted much attention from both researchers and practitioners. How to evaluate the risk control of supply chains plays an important role to meet the requirement of diverse customers. Knowledge-based risk control evaluation shares the real-time supply chain knowledge for decision-making. This paper proposes a risk control evaluation model for supply chains based on knowledge management. It contains three sub-systems: 1) supply chain custom system, which gathers and monitors supply chain risk information; 2) supply chain knowledge system, which communicates, associates, cooperates and masters the knowledge in use of risk control based on established index system; 3) decision-making control and feedback system, which performs decision evaluation based on fuzzy inference to make the decision-making competitive. A risk control evaluation case study demonstrates that our methods significantly evaluates the supply chain risk control performance in terms of accuracy compared with expert judgment.

The risk control evaluation for supply chain based on knowledge management

The supply chain risk control has recently attracted much attention from both researchers and practitioners. How to evaluate the risk control of supply chains plays an important role to meet the requirement of diverse customers. Knowledge-based risk control evaluation shares the real-time supply chain knowledge for decision-making. This paper proposes a risk control evaluation model for supply chains based on knowledge management. It contains three sub-systems: 1 supply chain custom system, which gathers and monitors supply chain risk information; 2 supply chain knowledge system, which communicates, associates, cooperates and masters the knowledge in use of risk control based on established index system; 3 decision-making control and feedback system, which performs decision evaluation based on fuzzy inference to make the decision-making competitive. A risk control evaluation case study demonstrates that our methods significantly evaluates the supply chain risk control performance in terms of accuracy compared with expert judgment.

Designing a generic human-machine framework for real-time supply chain planning

Abstract Mixed-Initiative-Systems (MIS) are hybrid decision-making systems in which human and machine collaborate in order to produce a solution. This paper described an MIS adapted to business optimization problems. These problems can usually be solved in less than an hour as they show a linear structure. However, this delay is unacceptable for iterative and interactive decision-making contexts where users need to provide their input. Therefore, we propose a system providing the decision-makers with a convex hull of optimal solutions that minimize/maximize the variables of interest. The users can interactively modify the value of a variable and the system is able to recompute a new optimal solution in a few milliseconds. Four real-time reoptimization methods are described and evaluated. We also propose an improvement to this basic scheme in order to allow a user to explore near-optimal solutions as well. Examples showing real case of how we have exploited this framework within interactive decision support software are given. Highlights A Mixed Initiative System adapted to business optimization problems is presented. Real-time reoptimization methods are described and evaluated. The system is able to recompute a new optimal solution in a few milliseconds. Improvement to this basic scheme allow a user to explore near-optimal solutions. Examples showing real case of exploiting this framework are given.

Novel, smart and RFID assisted critical temperature indicator for supply chain monitoring

In order to reduce food waste and meet the needs of the demanding modern consumer regarding the quality of food items, it is crucial to monitor the supply chain and storage conditions of perishable food products. Considering this scenario, temperature plays an important role on food safety and quality during storage and supply. In this work, a critical temperature indicator (CTI) based on a solvent melting point is developed. Furthermore, the present CTI working principle is improved by the use of microfluidics technology. As final result, a novel and functional CTI-smart sensor which combines irreversible visual color changes and radio frequency identification (RFID) technologies is achieved. Such CTI integrated to a RFID tag provides a unique advantage to monitor the supply chain in real time by the simple use of a RFID reader in strategic points.

Conceptual considerations for real-time supply chain efficiency monitoring

Conceptual considerations for real-time supply chain efficiency monitoring

A simulation-based decision support framework for real-time supply chain risk management

In today’s competitive and dynamic market conditions, Supply Chain Risk Management (SCRM) has become a key concern for organizations in order to respond effectively to market uncertainties and disruptions. There are several sources for supply chain risk such as process, control, demand, supply, and environment. Natural disaster and manmade crises have also put negative impact on the performance of supply chains. In addition, risk management in the supply chain is a challenge due to the fact that the time, place, and severity of risks are fairly unpredictable. Controlling and monitoring risk in real-time is critical to providing a quick response to unanticipated events in order to reduce the consequences of these events. Hence, there is an immediate need to incorporate the risk management, computer simulation, and real-time information systems into a framework to assist decision makers in evaluating and managing supply chain risks. This paper develops a framework for the design of a simulation-based decisi...

1102 リアルタイムサプライチェーン時代のEmotional Engineering

1102 リアルタイムサプライチェーン時代のEmotional Engineering

Real Time Supply Chain Management Co-Modeling of Total Supply Chain Solutions

The diversification of collaborations and the complexity of processes in the same Supply Chain Management (SCM) needs a powerful and a flexible Information System (IS). For that, the classic modeling solutions of information systems cannot satisfy all the constraints of the complex E-SCM. Furthermore, the total E-SCM with the two brands of information system and SCM require advanced methods for co-modeling of complex systems. For more implication of all SCM actors, we consider an integration and dynamic solution for the management of supply chain activities a good tendency to achieve all industries challenges. This paper presents an approach for the total real time supply chain management. We adopt a method based on co-modeling of distributed Information System (IS) architecture in complex supply chain management.

APPLICATION OF CONTROL THEORETIC TOOLS TO SUPPLY CHAIN DISRUPTION MANAGEMENT

Supply chain disruption management aims at real-time supply chain monitoring, alerting supply chain participants about deviations and possible disruptions as well as elaborating adjustment control actions. A basis for the alerting and disruption recovery is a tolerance area of execution parameters' admissible deviations. Two important questions still remain open: (i) how to determine the borders of the tolerance area and (ii) what adjustments steps should be taken to overcome a disruption. In this paper, we propose to use dynamic robustness analysis on the basis of attainable sets and the adaptive adjustment on the basis of positional optimization as an integrated framework to extend existing techniques. We consider supply chain robustness as a dynamic supply chain property that emerges through controlled adaptability on the basis of feedback loops. With the results of this study, the borders of deviations' sectors within the tolerance area can be determined. In each of these sectors, certain adjustment actions at different adaptation levels can be interrelated. Copyright © 2013 IFAC

Advanced Supply Chain Information for Rule-Based Sequence Adaptions on a Mixed-Model Assembly Line with Unreliable Just-In-Sequence Deliveries

The proliferation of just-in-sequence (JIS) deliveries has raised the vulnerability of assemblies to costly production stoppages or rework due to missing components. Through a comprehensive real-time supply chain monitoring systems, these supply issues can be detected early and affected orders removed from planned assembly sequences in time to avoid production disturbances. Using simulation analysis, this paper explores the impact of unreliable JIS deliveries and the mitigation potential of transparent supply chains that allow a rule-based order resequencing on a mixed-model assembly line. The results indicate that (i) rework due to unreliable JIS deliveries can be eliminated and (ii) the trade-off between schedule nervousness and optimality can be balanced, making the proposed rule a feasible approach.

Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion

The revolution of Internet-of-Things (IoT) is reshaping the modern food supply chains with promising business prospects. To be successful in practice, the IoT solutions should create "income-centric" values beyond the conventional "traceability-centric" values. To accomplish what we promised to users, sensor portfolios and information fusion must correspond to the new requirements introduced by this income-centric value creation. In this paper, we propose a value-centric business-technology joint design framework. Based on it the income-centric added-values including shelf life prediction, sales premium, precision agriculture, and reduction of assurance cost are identified and assessed. Then corresponding sensor portfolios are developed and implemented. Three-tier information fusion architecture is proposed as well as examples about acceleration data processing, self-learning shelf life prediction and real-time supply chain re-planning. The feasibilities of the proposed design framework and solution have been confirmed by the field trials and an implemented prototype system.

Smart supplier selection based on voice of customer using an integrated bidding mechanism in real-time

The most critical issues in devising an agent-based evaluation engine have been comprehensively discussed here; at first, an autonomous real-time supply chain coordination system is introduced. Next, the configuration of an evaluation agent and its assessment engine are explained. The main idea is the smart module to be applied by the evaluation agent to pick the best supplier’s bid(s). This hybrid model is composed of three useful tools: fuzzy logic, analytical hierarchical process, and quality function deployment and works without human intervention. The approach has been carefully implemented and verified via a real-world case study in a medium-to-large industry manufacturing vehicle tires and other rubber products. A collection of twelve assessment criteria classified in two categories has been considered. Eight factors are derived from customer suggestions and the other four are design specifications required to manufacture the product. The most important advantages of this work over earlier researches on supplier selection are: implementation of an autonomous assessment mechanism using intelligent agents for the first time, making the best out of three widely applied methodologies all at once, evaluation process mainly based on features of customer order, coordination of supply job based on a bidding system, and portal-mediated operation and control via softbots. Key words: Supply chain coordination, bidding mechanism, agent-based systems, fuzzy logic, business automation, group decision making, smart algorithm.

Applicability of optimal control theory to adaptive supply chain planning and scheduling

Decisions in supply chain planning and control are interconnected and depend on tackling uncertainties and dynamics. From this perspective, control theory (CT) is an interesting research avenue for the supply chain management (SCM). In this paper, the applicability of optimal CT to SCM is investigated. Our analysis is based on the fundamentals of control and systems theory and experimental modeling. The paper describes important issues and perspectives that delineate dynamics in supply chains, identifies and systemizes different streams in application of CT to production, logistics, and SCM in the period from 1960 to 2011. It derives some classifications, performs a critical analysis, and discusses further researches. Some drawbacks and missing links in the literature are pointed out. Several crucial application areas of control theory to SCM are discussed. Subsequently, optimal program control, challenges and advantages of its application in the SCM are addressed. It is shown how optimal program control can be applied to adaptive supply chain planning. In addition, it is concluded that with the help of CT, robustness, adaptability, and resilience of supply chains can be investigated in their consistency with operations planning and execution control within a conceptually and mathematically integrated framework. However, although SCs resemble control systems, they have some peculiarities which do not allow a direct application of CT methods. In this setting, further development of interdisciplinary approaches to supply chain optimization is argued. An extended co-operation between control and supply chain experts may have the potential to introduce more realism to the dynamic planning and models and improve real-time supply chain control policies.

An advanced adoption model and an algorithm of evaluation agents in automated supplier ranking

Intelligent evaluation agent has been the most recent attempt toward automated supplier bid selection based on customer preferences. It has been proven to have advantages for successful supply chain coordination. Based on a formerly implemented real-time supply chain coordination system using intelligent agents, this work further investigates the problem to devise an intelligent fuzzy algorithm to evaluate supplier bids without direct human intervention. The general decision model of agent technology adoption has been explained in detail to provide a roadmap for managers and engineers in their movement toward multi-agent working environments. Then, the hybrid evaluation mechanism has been discussed step-by-step. Afterward, the approach has been carefully implemented and verified via a real-world case study. In this regard, a collection of twelve assessment criteria classified in two categories of customer suggestions and design specifications have been considered. This work has key advantages over earlier ones, including: modeling agent technology adoption in supply networks, description of an autonomous assessment mechanism using intelligent agents, making the best out of three useful methodologies of F-AHP-QFD, considering features of customer order and his/her preferences throughout the decision making process, and coordination of supply processes using a bidding system based on pervasive and ubiquitous computing mechanisms.

Simulating A State Of The Art Agent Based System With Fuzzy Reasoning For Supply Chain Coordination

With the emergence of high speed wireless networks and parallel advancements in Internet based technologies such as the Semantic Web, Web Services, Multi Agent Systems, and Context Awareness, the realization of the vision of the intelligent wireless web (IWW) has become a possibility. On the other side, recent developments in the field of multi criteria decision making, have led us to more accurate and applicable algorithms. In this paper, we are going to summarize the details and results of a multidisciplinary agent based software, namely SWESS that enables real-time supply chain coordination through taking advantage of different methods of different scientific areas such as computer science, supply chain management and multi criteria decision making.

Supporting real-time supply chain decisions based on RFID data streams

While RFID technology has been widely praised for its ability to streamline supply chain processes, little attention has been given to its unique data capturing characteristics to support real-time decision making. Being able to efficiently perform complex real-time analysis on top of RFID event streams is a key challenge for modern applications. This provides management with a novel data analysis mechanism to allow better, tactical, on time, well-informed decisions. The two main issues in RFID data management (RFDM) concern expressibility (how to simply and concisely express stream queries) and performance (how to efficiently evaluate stream queries). In this paper we claim that a spreadsheet-like query model, where formulation is done in a column-wise fashion, can express intuitively a large class of useful and practical RFDM queries. We propose a simple SQL extension to do that and show how these queries can be evaluated efficiently. We finally discuss a prototype called COSTES (COntinuous SpreadsheeT-likE computations), which implements our SQL extensions and evaluation algorithms. Presentation takes place within the context of two representative RFID applications, namely shelf availability and in-store sales promotions.

Robust supply chain performance via Model Predictive Control

This paper presents a novel robust Model Predictive Control (MPC) method for real-time supply chain optimization under uncertainties. This method optimizes the closed-loop economic performance of supply chain systems and addresses different sources of uncertainties located external to and within the feedback loop. The future system behavior is predicted by a closed-loop model, which includes both the open-loop system model and a controller model described by an optimization problem. The robust MPC formulation involves the solution of a constrained, bi-level stochastic optimization problem, which is transformed into a tractable problem involving a limited number of deterministic conic optimization problems solved reliably using an interior point method. The robust controller is applied to a real industrial multi-echelon supply chain optimization problem, and its performance is shown to reduce stock-outs without excessive inventories.

Initiating a state of the art system for real-time supply chain coordination

Intelligent Wireless Web (IWW) employs the capabilities of high speed wireless networks and exploits the parallel advancements in Internet-based technologies such as the Semantic Web, Web Services, Agent-based Technologies, and context awareness. Considering its great potentials to be applied in business systems, we have devised an innovative model, based on the IWW services, for a typical mobile real-time supply chain coordination system which has been developed and tested in a real operational environment. Our article investigates the proposed system in this way: at the start, the building blocks of the IWW are discussed in detail. Then, we fully explain the basic concepts of mobile real-time supply chain coordination and concentrate on the motivations to implement such a modern system. The vision of intelligent wireless web services, as discussed in this paper, centers on the need to provide mobile supply chain members highly specific data and services in real-time on an as-needed basis, with the flexibility of use for the user. In this regard, we investigate nine enabling technologies of the IWW for our system and discuss how, by exploiting the convergence and synergy between different technologies, it has become possible to deliver intelligent wireless web support to mobile real-time supply chain coordination. Afterwards, a practical framework is clearly established in four phases. This initiative system has been implemented in the laboratory and has passed the evaluation processes successfully. Further details will be announced in near future in another research article.