Tai-Woo Chang

An integrative framework for supplier relationship management

Purpose – There have been many studies on topics related to supplier relationship management (SRM), namely purchasing strategy, supplier selection and development, and collaboration with suppliers. However, these studies have not suggested a solution based on an integrative concept, as they focus only on domain‐specific problems. To overcome this limitation, the purpose of this present paper is to suggest a framework for an integrative SRM system by analyzing comprehensive approaches to overall SRM functions. Design/methodology/approach – The paper reviewed and analyzed studies related to SRM from an integrative viewpoint, proposed a framework for an integrative SRM system, and performed a case study based on the analytical hierarchy process with a field survey. Findings – The paper expects that the proposed framework can play a major role in enhancing the efficiency and effectiveness of SRM by adopting an integrative concept because the functions of SRM are highly interrelated. Furthermore, it verifies the applicability of the framework via a case study. Research limitations/implications – Not many approaches are available for organizing evaluators or evaluation sheets, which are used for selecting criteria, providing weight, and evaluating supplier performance, that can secure objectivity of the evaluation; thus, when applying this framework to the industry, special consideration is needed. Practical implications – The proposed framework allows the purchasing members to scrutinize key features of SRM before and during the SRM system operation. Originality/value – The paper provides useful knowledge about the role of SRM systems by holistically approaching SRM‐related processes while suggesting criteria and recommendations to a purchasing manager.

Developing performance measurement system for Internet of Things and smart factory environment

To cope with large fluctuations in the demand of a commodity, it is necessary for the manufacturing system to have rapid reactive ability. This requirement may be secured by performance measurement. Although manufacturing companies have used information systems to manage performance, there has been the difficulty of capturing real-time data to depict real situations. The recent development and application of the Internet of Things (IoT) has enabled the resolution of this problem. In demonstration of the functionality of IoT, we developed an IoT-based performance model consistent with the ISA-95 and ISO-22400 standards, which define manufacturing processes and performance indicator formulas. The development comprised three steps: (1) Selection of the Key Performance Indicators of the Overall Equipment Effectiveness (OEE), and the development of an IoT-based production performance model, (2) Implementation of the IoT-based architecture and performance measurement process using Business Process Modelling and (3) Validation of the proposed model through virtual factory simulation. We investigated the effect of the IoT-workability on the OEE, based on the final results of the simulation, both for the planned and actual productions. The simulation results showed that the proposed model represented the timestamp data acquired by IoT and captured the entire production process, thus enabling the determination of real-time performance indicators.

A development methodology for e-Work ontology using RDF/RDFS and PSL

The information sources for the e-Work environment are heterogeneous and distributed, and their contents are not machine-understandable. In this article, in order to integrate the syntax and the semantics of this information, we propose a development methodology for e-Work ontology using Resource Description Framework (RDF), RDF Schema (RDFS) and Process Specification Language (PSL). In a layered architecture, we use RDF/RDFS for the data of resources and the taxonomy of the PSL-ontology terms, and we use PSL, which is represented as eXtensible Markup Language (XML), for the process and the inference of the meaning of it. In this way, we can present an integrated representation of the data and the process in the distributed environment of e-Work. We illustrate the ontology building methodology by giving an example of e-Work scenario and application procedure, which is quoted from the RosettaNet e-Business standard and concerns order management, such as quotation and purchase order. The ontology is applied to the scenario.

A Model and Analysis of the Bullwhip Effect Using a SCOR-Based Framework

Increasing dynamics are making efficient management of the supply chain difficult. The bullwhip effect is known to be a major source of this inefficiency so there is a considerable amount of literature analyzing its causes. However, the reported outcomes are not comparable because they consider different business environments and make different assumptions regarding operative processes. We propose a SCOR (Supply-Chain Operations Reference-model)-based framework for modeling and analyzing the bullwhip effect so that practitioners can evaluate the performance of their supply chain, and establish a strategy to improve its performance.

Camera Placement in Smart Cities for Maximizing Weighted Coverage With Budget Limit

This paper addresses the camera placement problem for smart cities in 3-D space and proposes a heuristic algorithm that maximizes the weighted coverage rate while satisfying the budget constraint. We first discuss about the quantization of surveillance target and camera locations into discrete grid points and the setting of the weights of target grid points. We then present the visibility analysis with field of view in consideration of occlusions and different camera specifications. Based on these characteristics and constraints, we formulate the camera placement problem and propose a new heuristic algorithm called collaboration-based local search algorithm, which incorporates the local search into collaborative allocation. We evaluate the performance of the proposed algorithm in comparison with the greedy algorithm, binary genetic algorithm, and binary particle swarm optimization through simulation experiments with small and large problem sets. The simulation results show that the proposed algorithm outperforms the three existing algorithms in terms of the average weighted coverage rate and computation time.

Business Process Patterns for Integrated Supply Chain Planning

Todays competitive global market makes most enterprise endeavor to specialize their business areas, and co-operate with trading partners in supply chain by forms of collaboration, information and business process sharing. However, even the supply chain plan generated by co-operation often fails to be executed successfully, because it was generated without capacities of suppliers and more over nested suppliers. To overcome this limitation, the supply chain plan should be generated truly integrated way. In this paper, we classify business patterns based on scenarios, and present business process models about them. In addition, we describe the types of supply chain planning problem.