A multiple-vendor single-buyer integrated inventory model with a variable number of vendors

Supply chain management is concerned with the coordination of material and information flows in multi-stage production systems. A closer look at the literature reveals that previous research on the coordination of multi-stage production systems has predominantly focused on the sales side of the supply chain, whereas problems that arise on the supply side have often been neglected. This article closes this gap by studying the coordination of a supplier network in an integrated inventory model. Specifically, we consider a buyer sourcing a product from heterogeneous suppliers and tackle both the supplier selection and lot size decision with the objective to minimise total system costs. First, we provide mathematical formulations for the problem under study, and then suggest a two-stage solution procedure to derive a solution. Numerical studies indicate that our solution procedure reduces the total number of supplier combinations that have to be tested for optimality, and that it may support initiatives which aim on increasing the efficiency of the supply chain as a heuristic planning tool.     

Integrierte Informationsversorgung zur Entscheidungsunterstützung in Netzgesellschaften

Increasing regulatory requirements such as price cap regulation have increased the importance of strategic grid asset management. Empirical studies reveal that information supply and consolidation are error prone and long-term processes. The reason is the missing automation of extraction, transformation, and loading. The current gap does neither fulfill the requirements of regulatory nor the necessity of standardized reporting. Furthermore, a detailed planning is not enabled and the calculation of key figures is extensive. Currently, a framework that considers the coupling of financial and technical key figures, the coupling of strategic and operative key figures as well as the integration into information systems is not existent. Therefore, this paper addresses the design of a reference model as a recommendation for action to integrate the asset management within information systems. It is validated by expert interviews. Moreover, it provides information to integrate relevant financial and technical artifacts from distributed systems. Simultaneously it provides recommendations for implementing Business Intelligence in the context of strategic decision support.     

Sourcing strategies in supply risk management: An approximate dynamic programming approach

In recent years, supply chains have become increasingly globalized. As a consequence, the world's supply of all types of parts has become more susceptible to disruptions. Some of these disruptions are extreme and may have global implications. Our research is based on the supply risk management problem faced by a manufacturer. We model the problem as a dynamic program, design and implement approximate dynamic programming (ADP) algorithms to solve it, to overcome the well-known curses of dimensionality. Using numerical experiments, we compare the performance of different ADP algorithms. We then design a series of numerical experiments to study the performance of different sourcing strategies (single, dual, multiple, and contingent sourcing) under various settings, and to discover insights for supply risk management practice. The results show that, under a wide variety of settings, the addition of a third or more suppliers brings much less marginal benefits. Thus, managers can limit their options to a backup supplier (contingent sourcing) or an additional regular supplier (dual sourcing). Our results also show that, unless the backup supplier can supply with zero lead time, using dual sourcing appears to be preferable. Lastly, we demonstrate the capability of the proposed method in analyzing more complicated realistic supply chains.     

The credit game on network supplier and customer based on big data

In this paper, we make B2C transaction as the research object, to analyze the transaction credit game on network supplier and customer based on big data. In the condition of considering the cost of B2C network supplier improving commodity credit, and the cost of B2C customer analyzing and managing network supplier commodity credit big data, constructing the credit game relationship model, analyzing the game process and the influence factors, and simulating the game process using System Dynamics theory model. The research only is a part of the research on B2C network supplier and customer transaction credit relationship, and is a part of the research on B2C network supplier and customer transaction process in big data environment, this paper is only to illustrate the variation that big data bring to B2C network supplier and customer transaction behavior. To the application and research of big data in network transaction credit management, this paper research result has a certain reference value.     

A fit-gap analysis of e-business curricula and job demand in Taiwan and the US

During the past decade, many enterprises have been re-directing their resources into critical business areas to keep up with economic and market changes. They have adopted electronic business (EB) systems, such as supply chain management, enterprise resource planning (ERP), and enterprise application integration (EAI), to ensure seamless integration with internal processes as well as suppliers and customers. This phenomenon indicates that EB systems are playing an important role in attaining the effectiveness of enterprise operations. However, there is a constant complaint from recruiters that EB professionals with the right skills are hard to come by. To gauge the rapid changes in EB education and industry demand, EB curricula from top universities and job announcements from popular career Web sites in both the US and Taiwan are collected. We analyze the data and compare the results between the two countries to recommend remedial actions for narrowing the gap between industry and academia.     

Data management challenges and development for military information systems

This paper explores challenges facing information system professionals in the management of data and knowledge in the Department of Defense (DOD), particularly in the information systems utilized to support command, control, communications, computers, and intelligence (C/sup 4/ I). These information systems include operational tactical systems, decision-support systems, modeling and simulation systems, and nontactical business systems, all of which affect the design, operation, interoperation, and application of C/sup 4/ I systems. Specific topics include issues in integration and interoperability, joint standards, data access, data aggregation, information system component reuse, and legacy systems. Broad technological trends, as well as the use of specific developing technologies are discussed in light of how they may enable the DOD to meet the present and future information-management challenges.     

Challenges for the cyber-physical manufacturing enterprises of the future

This paper summarizes a vision of the challenges facing the so-called “Industry of the Future” as studied by the research community of the IFAC Coordinating Committee 5 on Manufacturing and Logistics Systems, which includes four Technical Committees (TC). Each TC brings its own vision and puts forward trends and issues important and relevant for future research. The analysis is performed on the enterprise-level topics with an interface too other relevant systems (e.g., supply chains). The vision developed might lead to the identification of new scientific control directions such as Industry 4.0 technology-enabled new production strategies that require highly customised supply network control, the creation of resilient enterprise to cope with risks, developments in management decision-support systems for the design, and scheduling and control of resilient and digital manufacturing networks, and collaborative control. Cobots, augmented reality and adaptable workstations are a few examples of how production and logistic systems are changing supporting the operator 4.0. Sustainable manufacturing techniques, such closed-loop supply chains, is another trend in this area. Due to increasing number of elements and systems, complex and heterogeneous enterprise systems need to be considered (e.g., for decision-making). These systems are heterogeneous and build by different stakeholders. To make use of these, an environment is needed that allows the integration of the systems forming a System-of-Systems (SoS). The changing environment requires models which adapt over time. Some of the adaptation is due to learning, other mechanisms include self-organisation by intelligent agents. In general, models and systems need to be modular and support modification and (self-)adaptation. An infrastructure is needed that supports loose coupling and evolving systems of systems. The vision of the overall contribution from the research community in manufacturing and logistics systems, over the next few years is to bring together researchers and practitioners presenting and discussing topics in modern manufacturing modelling, management and control in the emerging field of Industry 4.0-based resilient and innovative production SoS and supply networks.     

Enterprise systems and demand chain management: a cross-sectional field study

Increased product variety, compressed cycle times, supply chain network based competition and the uncertainty in business environment are forcing organizations to shift their emphasis towards demand chain management. Though enterprise systems and supply chain management software solutions are well in place in most of the large enterprises in Australia, their ability to support demand chain management approach is not yet known. This paper investigates the adoption of demand chain management in Australian organizations using cross-sectional qualitative field study. It found that the adoption is limited despite the organizational capabilities and sound digital platforms. Standardization, integration, visibility and control of processes and information, enabled by enterprise systems, are helping the organizations in improving their ability to sense and shape market demand and customer needs, and build agility into their decision making processes. Attempts to synchronise operating and finance cycles and collecting market intelligence and sharing of that across the supply chain are some of the initiatives that have started showing benefits. Adopting the demand chain management initiatives such as establishment of market intelligence mechanism, building agility into decision making processes, sophisticated usage of optimization tools embedded in software solutions, and process frameworks such as Supply Chain Operations Reference are helping organizations to achieve both agility and control simultaneously.     

A research agenda for query processing in large-scale peer data management systems

Peer Data Management Systems (Pdms) are a novel, useful, but challenging paradigm for distributed data management and query processing. Conventional integrated information systems have a hierarchical structure with an integration component that manages a global schema and distributes queries against this schema to the underlying data sources. Pdms are a natural extension to this architecture by allowing each participating system (peer) to act both as a data source and as an integrator. Peers are interconnected by schema mappings, which guide the rewriting of queries between the heterogeneous schemas, and thus form a P2P (peer-to-peer)-like network.Despite several years of research, the development of efficient Pdms still holds many challenges. In this article we first survey the state of the art on peer data management: We classify Pdms by characteristics concerning their system model, their semantics, their query planning schemes, and their maintenance. Then we systematically examine open research directions in each of those areas. In particular, we observe that research results from both the domain of P2P systems and of conventional distributed data management can have an impact on the development of Pdms.     

Recent Advances in Mobile Grid and Cloud Computing

Grid and cloud computing systems have been extensively used to solve large and complex problems in science and engineering fields. These systems include powerful computing resources that are connected through high-speed networks. Due to the recent advances in mobile computing and networking technologies, it has become feasible to integrate various mobile devices, such as robots, aerial vehicles, sensors, and smart phones, with grid and cloud computing systems. This integration enables the design and development of the next generation of applications by sharing of resources in mobile environments and introduces several challenges due to a dynamic and unpredictable network. This paper discusses applications, research challenges involved in the design and development of mobile grid and cloud computing systems, and recent advances in the field.     

Business process integration as a solution to the implementation of supply chain management systems

In the domain of supply chain management (SCM), various software packages have been developed for planning business strategies. To solve the problem of system productivity in applying planning packages, we propose a solution concept, business process integration (BPI), which fuses workflow and enterprise application integration (EAI) technology. Two characteristic policies are included in BPI. The first is to design the minimum set of business processes for real-time information sharing with planning packages without changing other processes. The second is to integrate several systems with EAI technology and to manage their execution with a workflow tool. Based on these policies, we propose various design templates and integration adapters. Our evaluation shows that using BPI, a target system can be developed with less manpower, in less time, and with higher quality than previous methods.     

Secure network coding for wireless mesh networks: Threats, challenges, and directions

In recent years, network coding has emerged as a new communication paradigm that can significantly improve the efficiency of network protocols by requiring intermediate nodes to mix packets before forwarding them. Recently, several real-world systems have been proposed to leverage network coding in wireless networks. Although the theoretical foundations of network coding are well understood, a real-world system needs to solve a plethora of practical aspects before network coding can meet its promised potential. These practical design choices expose network coding systems to a wide range of attacks.We identify two general frameworks (inter-flow and intra-flow) that encompass several network coding-based systems proposed in wireless networks. Our systematic analysis of the components of these frameworks reveals vulnerabilities to a wide range of attacks, which may severely degrade system performance. Then, we identify security goals and design challenges in achieving security for network coding systems. Adequate understanding of both the threats and challenges is essential to effectively design secure practical network coding systems. Our paper should be viewed as a cautionary note pointing out the frailty of current network coding-based wireless systems and a general guideline in the effort of achieving security for network coding systems.     

DRP分销管理系统的设计与实现

DRP是管理企业的分销网络系统,目的是使企业具有对订单和供货具有快速反应和持续补充库存的能力。通过互联网将供应商与经销商有机地联系在一起,DRP为企业的业务经营及与贸易伙伴的合作提供了一种全新的模式。该文使用Java作为开发语言,采用Struts2框架技术搭建整个系统,数据库采用SQL2000,Eclipse5.1[1]作为开发工具,设计并实现了DRP分销管理系统。     

Toward a cloud-based manufacturing execution system for distributed manufacturing

This paper illustrates the needs and challenges for the management of distributed manufacturing in a multi-company supply chain and processes these further as features of new IT systems. Requirements are collected from manufacturing companies and combined with insights from literature in the field of current ERP/MES system drawbacks, advantages, needs and challenges. The findings show that the needs and challenges in data integration inside SME networks are closely related to the limitations of current supply chain solutions. Current ERP-solutions lack extended enterprise support and a shared cloud-based approach. On the other hand, current MES solutions can operate the manufacturing process, but not for distributed manufacturing. As an answer to the requirements, we made a proposal for the core of architecture for next generation of MES solution in this position paper. Moreover, a pilot software tool has been developed to support the needs related to real time, cloud-based, light weight operation.     

A Survey of Non-Volatile Main Memory Technologies: State-of-the-Arts,Practices, and Future Directions

Non-Volatile Main Memories(NVMMs)have recently emerged as a promising technology for future memory systems.Generally,NVMMs have many desirable properties such as high density,byte-addressability,non-volatility,low cost,and energy efficiency,at the expense of high write latency,high write power consumption,and limited write endurance.NVMMs have become a competitive alternative of Dynamic Random Access Memory(DRAM),and will fundamentally change the landscape of memory systems.They bring many research opportunities as well as challenges on system archi-tectural designs,memory management in operating systems(OSes),and programming models for hybrid memory systems.In this article,we first revisit the landscape of emerging NVMM technologies,and then survey the state-of-the-art studies of NVMM technologies.We classify those studies with a taxonomy according to different dimensions such as memory ar-chitectures,data persistence,performance improvement,energy saving,and wear leveling.Second,to demonstrate the best practices in building NVMM systems,we introduce our recent work of hybrid memory system designs from the dimensions of architectures,systems,and applications.At last,we present our vision of future research directions of NVMMs and shed some light on design challenges and opportunities.     

Fuzzy DEMATEL method for developing supplier selection criteria

Supply chain management (SCM) practices have flourished since the 1990s. Enterprises realize that a large amount of direct and indirect profits can be obtained from effective and efficient SCM practices. Supplier selection has great impact on integration of the supply chain relationship. Effective and accurate supplier selection decisions are significant components for productions and logistics management in many firms to enhance their organizational performance. This study pioneers in using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method to find influential factors in selecting SCM suppliers. The DEMATEL method evaluates supplier performance to find key factor criteria to improve performance and provides a novel approach of decision-making information in SCM supplier selection. This research designs a fuzzy DEMATEL questionnaire sent to seventeen professional purchasing personnel in the electronic industry. Our research results find that stable delivery of goods is the most influence and the strongest connection to other criteria.     

Structured methodology for supplier selection and evaluation in a supply chain

Supply chain management (SCM) is one of the most important competitive strategies used by modern enterprises. The main aim of supply chain management is to integrate various suppliers to satisfy market demand. Meanwhile, supplier selection and evaluation plays an important role in establishing an effective supply chain. Traditional supplier selection and evaluation methods focus on the requirements of single enterprises, and fail to consider the entire supply chain. Therefore, this study proposes a structured methodology for supplier selection and evaluation based on the supply chain integration architecture.In developing the methodology for supplier selection and evaluation in a supply chain, enterprise competitive strategy is first identified using strengths weaknesses opportunities threats (SWOT) analysis. Based on the competitive strategy, the criteria and indicators of supplier selection are chosen to establish the supplier selection framework. Subsequently, potential suppliers are screened through data envelopment analysis (DEA). Technique for order preference by similarity to ideal solution (TOPSIS), a multi-attribute decision-making (MADA) method is adapted to rank potential suppliers. Finally, the Taiwanese textile industry is used to illustrate the application and feasibility of the proposed methodology.This study facilitates the improvement of collaborator relationships and the management of potential suppliers to help increase product development capability and quality, reduce product lifecycle time and cost, and thus increase product marketability.     

User,Use & Utility Research

Business and Information Systems Engineering (BISE) is at a turning point. Planning, designing, developing and operating IT used to be a management task of a few elites in public administrations and corporations. But the continuous digitization of nearly all areas of life changes the IT landscape fundamentally. Success in this new era requires putting the human perspective – the digital user – at the very heart of the new digitized service-led economy. BISE faces not just a temporary trend but a complex socio-technical phenomenon with far-reaching implications. The challenges are manifold and have major consequences for all stakeholders, both in information systems and management research as well as in practice. Corporate processes have to be re-designed from the ground up, starting with the user’s perspective, thus putting usage experience and utility of the individual center stage. The digital service economy leads to highly personalized application systems while organizational functions are being fragmented. Entirely new ways of interacting with information systems, in particular beyond desktop IT, are being invented and established. These fundamental challenges require novel approaches with regards to innovation and development methods as well as adequate concepts for enterprise or service system architectures. Gigantic amounts of data are being generated at an accelerating rate by an increasing number of devices – data that need to be managed. In order to tackle these extraordinary challenges we introduce ‘user, use & utility’ as a new field of BISE that focuses primarily on the digital user, his or her usage behavior and the utility associated with system usage in the digitized service-led economy. The research objectives encompass the development of theories, methods and tools for systematic requirement elicitation, systems design, and business development for successful Business and Information Systems Engineering in a digitized economy – information systems that digital users enjoy using. This challenge calls for leveraging insights from various scientific disciplines such as Design, Engineering, Computer Science, Psychology and Sociology. BISE can provide an integrated perspective, thereby assuming a pivotal role within the digitized service led economy.     

A survey on control theory applications to operational systems,supply chain management,and Industry 4.0

Modern production and logistics systems, supply chains, and Industry 4.0 networks are challenged by increased uncertainty and risks, multiple feedback cycles, and dynamics. Control theory is an interesting research avenue which contributes to further insights concerning the management of the given challenges in operations and supply chain management. In this paper, the applicability of control theory to engineering and management problems in supply chain operations is investigated. Our analysis bridges the fundamentals of control and systems theory to supply chain and operations management. This study extends our previous survey in the Annual Reviews in Control (Ivanov et al. 2012) by including new literature published in 2012–2018, identifying two new directions of control theory applications (i.e., ripple effect analysis in the supply chains and scheduling in Industry 4.0) and analysis towards the digital technology use in control theoretic models. It describes important issues and perspectives that delineate dynamics in supply chains, operations, and Industry 4.0 networks and identifies and systemizes different streams in the application of control theory to operations and supply chain management and engineering in the period from 1960–2018. It updates the existing applications and classifications, performs a critical analysis, and discusses further research avenues. Further development of interdisciplinary approaches to supply chain optimization is argued. An extended cooperation between control engineers and supply chain experts may have the potential to introduce more realism to dynamic planning and models, and improve performance in production and logistics systems, supply chains, and Industry 4.0 networks. Finally, we analyze the trends towards the intellectualization of control and its development towards supply chain control analytics.     

Cyber-physical systems challenges: a needs analysis for collaborating embedded software systems

Embedding computing power in a physical environment has provided the functional flexibility and performance necessary in modern products such as automobiles, aircraft, smartphones, and more. As product features came to increasingly rely on software, a network infrastructure helped factor out common hardware and offered sharing functionality for further innovation. A logical consequence was the need for system integration. Even in the case of a single original end manufacturer who is responsible for the final product, system integration is quite a challenge. More recently, there have been systems coming online that must perform system integration even after deployment—that is, during operation. This has given rise to the cyber-physical systems (CPS) paradigm. In this paper, select key enablers for a new type of system integration are discussed. The needs and challenges for designing and operating CPS are identified along with corresponding technologies to address the challenges and their potential impact. The intent is to contribute to a model-based research agenda in terms of design methods, implementation technologies, and organization challenges necessary to bring the next-generation systems online.