Supply chain management information systems capabilities. An exploratory study of electronics manufacturers

Supply Chain Management Information Systems (SCM IS) play an increasingly critical role in the ability of firms to reduce costs and increase the responsiveness of their supply chain. This paper develops an empirically supported model of the organizational capabilities enabled by SCM IS. The model integrates and enriches theoretical and empirical studies of competitive strategy, supply chain management, and interorganizational information systems. Evidence from an exploratory case study of three large firms in the electronics manufacturing industry is examined to build a better-supported theory of SCM IS capabilities. The findings suggest the organizational capabilities enabled by SCM IS can be conceptualized as the level of support provided for: operational efficiency; operational flexibility; internal planning and analysis; and external planning and analysis. The theoretical model furthers an understanding of SCM IS capabilities and is sufficiently developed to permit operationalization for future studies evaluating the effectiveness of SCM IS.     

A computerized causal forecasting system using genetic algorithms in supply chain management

Forecasting activities are widely performed in the various areas of supply chains for predicting important supply chain management (SCM) measurements such as demand volume in order management, product quality in manufacturing processes, capacity usage in production management, traffic costs in transportation management, and so on. This paper presents a computerized system for implementing the forecasting activities required in SCM. For building a generic forecasting model applicable to SCM, a linear causal forecasting model is proposed and its coefficients are efficiently determined using the proposed genetic algorithms (GA), canonical GA and guided GA (GGA). Compared to canonical GA, GGA adopts a fitness function with penalty operators and uses population diversity index (PDI) to overcome premature convergence of the algorithm. The results obtained from two case studies show that the proposed GGA provides the best forecasting accuracy and greatly outperforms the regression analysis and canonical GA methods. A computerized system was developed to implement the forecasting functions and is successfully running in real glass manufacturing lines.     

A hierarchical framework for visualising and simulating supply chains in virtual environments

This paper presents research into applying virtual environment (VE) technology to supply chain management (SCM). Our research work has employed virtual manufacturing environments to represent supply chain nodes to simulate processes and activities in supply chain management. This will enable those who are involved in these processes and activities to gain an intuitive understanding of them, so as to design robust supply chains and make correct decisions at the right time. A framework system and its hierarchical structure for visualising and simulating supply chains in virtual environments are reported and detailed in this paper.     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

Setting order promising times in a supply chain network using hybrid simulation-analytical approach: An industrial case study

Supply chain management (SCM) involves the management of material and information flow among the members of chain such as vendors, manufacturing plants and distribution centers. The main processes in supply chain are production planning, control, distribution and logistics. Effective management of all these processes provides the manufacturing companies great advantages in time based competition. In order to gain a competitive edge, firms must be able to deliver their products fast and on-time. This can be managed by better production planning, scheduling and due-date setting. This paper suggests a hybrid approach for setting realistic order due dates for a produce-to-order manufacturing company operating within a supply chain environment. The proposed hybrid approach combines mathematical and simulation modeling to bring together the advantages of both approaches.     

Supply Chain Model for the Semiconductor Industry of Global Market

Supply chain management (SCM) is a new approach to satisfy customers of products and services via an integrated management for the whole business processes of the manufacturing from the raw material procurement to the product or service delivery to customers. With the rapid development of the information technology and global market environment the company is required to manage whole supply chain network to gain the competitiveness in business. Typically semiconductor industry is the one whose supply chain network is distributed all over the world, and its manufacturing process has the particular characteristics which has to be considered in the modeling of supply chain. In this paper we suggest the push and pull type supply chain models and their mathematical formulation for the semiconductor industry of the global market. Die bank between the front-end and back-end in the semiconductor manufacturing process is assumed to be the decoupling point by which two models are divided. Push supply chain model is based on the high throughput and the balance of the WIP flow, which takes the characteristics of re-entrant mechanism into account. Pull supply chain model is constructed considering order-based manufacturing, distribution and transportation process in order to meet customer's request appropriately. Development issues of the system and its implementation are also discussed.     

基于粗糙集的供应链绩效改进决策研究

从知识发现和数据挖掘的角度,利用粗糙集的理论和方法,建立了基于粗糙集的供应链绩效改进决策模型框架,并给出其中的指标约简方法和基于分辨矩阵计算指标权重的数学模型。最后结合一个制造业供应链绩效评价实例,首先对其基于平衡记分卡的指标体系进行了约简,然后建立了基于粗糙集的供应链绩效改进决策模型,确定了指标的客观权重。并对结果进行了分析,提出了绩效改进决策意见和措施。     

Relation model describing the effects of introducing RFID in the supply chain: evidence from the food and beverage industry in South Korea

The development of information technology has rapidly changed the logistics industry. RFID has become more and more important in the context of supply chain management (SCM), and implementation of RFID in SCM brings with it the potential to manage the information flow and to support communication and collaboration along the supply chain. This study was conducted to build a relation model, which is a structural model, to identify the effects of introducing RFID into the supply chain of the food and beverage industry in Korea. The supply chain of the food and beverage industry was divided into five activities: procurement, production, transport, sale, warehousing, and administration. This study was based on the premise that RFID will be embedded in a transport box or pallet circulated in the SC. The model showed that SC activities have positive relationships through the RFID system, and the introduction of RFID promotes information interchanges between SC activities, which in turn enable the coordination and consolidation of a total SCM. From the results of this study, it is expected that the RFID system does not only enable the SC partners to improve their utilities but also promotes the efficiency of SCM as a whole. This is meaningful considering that there is still a controversy regarding the effects of RFID on SCM.     

Web-service based architecture to support SCM context-awareness and interoperability

Integration of Web-Services and “smart objects” in supply chain manufacturing systems (SCM) enables enterprise innovation and competitiveness in a globalized economy. The paper proposes a web-service based architecture for SCM that enables enterprises to develop context-awareness and to achieve interoperability at data, services, processes and business levels using event based web service notifications. The architecture is analyzed and implemented following the case study of an enterprise in the automotive industry.     

过程工业供应链流结构及其管理研究

与离散制造业相比，过程工业具有大批量、连续性、高能耗等特点，根据过程工业的自身特点和复杂性，本文提出了过程工业供应链的概念，分别建立了组成该复杂供应链的物质流、能量流、信息流、资金流、工件流和人件流六大流的动态结构，并以此为基础，通过分析国内外过程工业供应链管理的研究和应用现状，建立了针对复杂过程系统的综合集成的过程工业供应链管理框架。     

Supervisory control of a multi-echelon supply chain: A modular Petri net approach for inter-organizational control

Petri nets (PNs) are frequently utilized to model system dynamics due to their ability to handle concurrencies and sequential dependence. In this paper, a portion of the supply chain operations reference (SCOR) model has been extracted and modeled using PNs for the purpose of exerting supervisory control upon a multi-echelon supply chain (SC). The activities of source, make and deliver, inherent in the SCOR model form the basis of the representation of the PN model for each echelon considered in the SC model. Two control nets are utilized: one above the base model of each echelon to exert local constraints and an enterprise level supply chain manager (SCM). The local constraints are at the tactical and operational levels while the SCM enforces additional constraints consisting of long term planning goals at the strategic level. Place invariants are used to create the supervisors. Performance measures of the total SC are formulated to determine the effectiveness of any partnership. An efficient method for finding the current state of the system is developed which is used to determine the performance measures of each echelon. This paper presents a modular approach to the overall structure and PN modeling for a SC system. It is intended to extend the use of supervisory control from a shop-floor level to an inter-organizational facility and enterprise level.     

CMieux: Adaptive strategies for competitive supply chain trading

Supply chains are a central element of today’s global economy. Existing management practices consist primarily of static interactions between established partners. Global competition, shorter product life cycles and the emergence of Internet-mediated business solutions create an incentive for exploring more dynamic supply chain practices. The supply chain trading agent competition (TAC SCM) was designed to explore approaches to dynamic supply chain trading between automated software agents. TAC SCM pits trading agents developed by teams from around the world against one another. Each agent is responsible for running the procurement, planning and bidding operations of a PC assembly company, while competing with others for both customer orders and supplies under varying market conditions. This paper presents Carnegie Mellon University’s 2005 TAC SCM entry, the CMieux supply chain trading agent. CMieux implements a novel approach for coordinating supply chain bidding, procurement and planning, with an emphasis on the ability to rapidly adapt to changing market conditions. We present empirical results based on 200 games involving agents entered by 25 different teams during what can be seen as the most competitive phase of the 2005 tournament. Not only did CMieux perform among the top five agents, it significantly outperformed these agents in procurement while matching their bidding performance. We also simulated 40 games against the best publicly available agent binaries. Our results show CMieux has significantly better average overall performance than any of these agents.     

Developing a supply chain disruption analysis model: Application of colored Petri-nets

As a result of globalization in the past two decades, supply chains are encountering more unknown conditions and risks. One important category of risks is disruptions that block material flowing through a supply chain and that may even result in end-product manufacturing failure. This paper uses a Petri nets-based model as a tool to understand the dissemination of disruptions and to trace the operational performance of a supply chain. The presented approach models how changes propagate through a supply chain and calculates the impact of disruptions on supply chain attributes by concluding the states that are obtainable from a given initial status in the supply chain.     

Effect of change management capability in real-time environment: an information orientation perspective in supply chain management

Supply chain management (SCM) is an important strategic tool that requires careful planning and management. While the availability of real-time information is a critical aspect of an SCM system, it possesses a potential to disrupt supply chain participants. Thus, the success of an SCM system hinges on how well participants deal with changes taking place in a real-time environment. This study adopts the concept of the real-time enterprise to understand the role of change management on SCM performance based on the concept of the information orientation. The study empirically validated the role of change management on SCM performance.     

A structural equation model for analyzing the impact of ERP on SCM

Enterprise resource planning (ERP) and supply chain management (SCM) represent important information technology investment options for operation or IT managers, and have been acclaimed in the practitioner and academic literature for their potential to improve business performance. The purpose of this article is to provide further insights into the adoption of ERP systems and the impacts on firm competence in SCM. We propose a model featuring ERP benefits to firm competences in supply chain management. We also hypothesize that three constructs of ERP benefits positively impact firm competences in SCM. To clarify the relationships among these constructs, structural equation model (SEM) is conducted to examine the model fit and nine hypotheses. The SEM results clearly demonstrate that there exist close interrelations among the benefits of implementing ERP systems and firm competences in SCM. The data from Taiwanese IT firms was collected through interviewing of experts and surveys. The results provide empirical evidence that the beneficial impacts of ERP on the supply chain do lead to better overall SCM competence. That evidence confirms that operational benefits, business process and management benefits, and strategic IT planning benefits of ERP in turn enhance firm competences of SCM in operational process integration, customer and relationship integration, and planning and control process integration.     

Fuzzy performance measurement of a supply chain in manufacturing companies

This paper is aimed to present a fuzzy decision making approach to deal with the performance measurement in supply chain systems. In the manufacturing environment, performance measurement is based on different quantitative and qualitative factors. Some of these factors may have a larger effect on the performance measure than others. Units of measure of the quantitative factors are different such as time, money, percentage, ratio, and counts. Thus, this paper presents a performance measurement approach based on fuzzy set theory and the pair-wise comparison of Analytical Hierarchy Process (AHP), which ensures the consistency of the designer’s assignments of importance of one factor over another to find the weight of each of the manufacturing activity in the departmental organization. In the proposed model, various input factors have been selected, and treated as a linear membership function of fuzzy type. It is tested on a numerical example. The approach provides an effective decision tool for the performance measurement of a supply chain in manufacturing environment.     

Supply chain management ontology from an ontology engineering perspective

Knowledge sharing and reuse are important factors affecting the performance of supply chains. These factors can be amplified in information systems by supply chain management (SCM) ontology. The literature provides various SCM ontologies for a range of industries and tasks. Although many studies make claims of the benefits of SCM ontology, it is unclear to what degree the development of these ontologies is informed by research outcomes from the ontology engineering field. This field has produced a set of specific engineering techniques, which are supposed to help developing quality ontologies. This article reports a study that assesses the adoption of ontology engineering techniques in 16 SCM ontologies. Based on these findings, several implications for research as well as SCM ontology adoption are articulated.     

Industrial digital ecosystems: Predictive models and architecture development issues

The concept of digital ecosystem (DES) is widely used in autonomous manufacturing process control and the development of complex, stable, interactive, self-organizing and reliable management systems for various industries. The paper offers a concept of DES control system architecture based on predictive models. For estimating and predicting the state of resources in production processes, an approach is developed using data mining based model generation. The paper also reviews the current state of research in the field of DES and their applications in supply chain management (SCM).     

Designing fuzzy-genetic learner model based on multi-agent systems in supply chain management

Supply chain requirements and challenges in recent years have made managers to explore new methods in dealing with supply chain management (SCM) problems. Methods with high flexibility which can adapt plans to real conditions help one to make a decision at the right time.In the SCM, distribution and allocation problems are of enormous significance and due to their applications in the cross-functional and final parts of SCM problems, they are in a particular position among the SCM problems.In this paper, by proposing an architecture based up on multi-agent system (MAS), a model is developed to tackle such problems as the nature of supply chain distributions, dynamic distributions systems (DS), uncertain parameters in DS, management of diverse objectives in DS, need for flexibility in DS and other factors considered as challenges and designing requirements in an agile model which can be all found in the SCM. MAS was used in this article owing to their special attributes and features. In MAS, each agent follows up a duty in a self-contained way and is able to adapt it to the environmental changes, after all helping the system to stay alive.     

Supply chain modeling in uncertain environment with bi-objective approach

Supply chain is viewed as a large-scale system that consists of production and inventory units, organized in a serial structure. Uncertainty is the main attribute in managing the supply chains. Managing a supply chain (SC) is very difficult, since various sources of uncertainty and complex interrelationships among various entities exist in the SC. Uncertainty may result from customer’s demand variability or unreliability in external suppliers. In this paper we develop an inventory model for an assembly supply chain network (each unit has at most one immediate successor, but any number of immediate predecessors) which fuzzy demand for single product in one hand and fuzzy reliability of external suppliers in other hand affect on determination of inventory policy in SCM. External supplier’s reliability has determined using a fuzzy expert system. Also the performance of supply chain is assessed by two criteria including total cost and fill rate. To solve this bi-criteria model, hybridization of multi-objective particle swarm optimization and simulation optimization is considered. Results indicate the efficiency of proposed approach in performance measurement.