Richard Ying Kit Fung, Shouju Ren, Jurgen Bode and Shaowu Luo
Analyses the environment and characteristics of an advanced manufacturing system (AMS). It is an open system with a multi‐layer structure and a self‐organizing ability capable of…
Abstract
Analyses the environment and characteristics of an advanced manufacturing system (AMS). It is an open system with a multi‐layer structure and a self‐organizing ability capable of responding to a continuous changing and unpredictable environment in this information age. Based on the analysis, summarizes the requirements of decision processes in a typical AMS, and presents a framework of a decision‐support system (DSS) in an advanced manufacturing enterprise. Outlines the conceptual modelling of the system, explains the work carried out by an inter‐disciplinary team composed of researchers from the 863/CIMS/I‐MADIS, a national hi‐tech R&D programme in China and a joint research programme in computer integrated manufacturing management between the City University of Hong Kong and Tsinghua University, Beijing. 863/CIMS is one of the subject themes under the auspices of automation technology of the National High Technology Research and Development Programme of China launched by the government in March 1986.
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Richard Y.K. Fung, Dave S.T. Law and W.H. Ip
Since imprecision, vagueness and ambiguity are often innate in human semantics, a flexible and tolerant method is needed to decode the voice of customer (VoC), so that the…
Abstract
Since imprecision, vagueness and ambiguity are often innate in human semantics, a flexible and tolerant method is needed to decode the voice of customer (VoC), so that the essential customer requirements can be identified and duly addressed. Quality function deployment (QFD) is a well‐known methodology for projecting the customer requirements onto the relevant design and production requirements and actions plan. This paper proposes an intelligent approach which extends the applications of QFD beyond its conventional boundary. The fuzzy inference technique is adopted to accommodate the possible imprecision and vagueness during VoC interpretation. The resulting model maps the customer requirements onto the relevant product attributes, taking into consideration their relationships and correlation during the inference process. The sub‐conclusions drawn from the fuzzy inference process are aggregated and defuzzified to yield the crisp design targets which can be used to guide the downstream manufacturing planning and control activities.
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Jin Wang and Richard Y.K. Fung
– The purpose of this paper is to maximize the expected revenue of the outpatient department considering patient preferences and choices.
Abstract
Purpose
The purpose of this paper is to maximize the expected revenue of the outpatient department considering patient preferences and choices.
Design/methodology/approach
Patient preference refers to the preferred physician and time slot that patients hold before asking for appointments. Patient choice is the appointment decision the patient made after receiving a set of options from the scheduler. The relationship between patient choices and preferences is explored. A dynamic programming (DP) model is formulated to optimize appointment scheduling with patient preferences and choices. The DP model is transformed to an equivalent linear programming (LP) model. A decomposition method is proposed to eliminate the number of variables. A column generation algorithm is used to resolve computation problem of the resulting LP model.
Findings
Numerical studies show the benefit of multiple options provided, and that the proposed algorithm is efficient and accurate. The effects of the booking horizon and arrival rates are studies. A policy about how to make use of the information of patient preferences is compared to other naive polices. Experiments show that more revenue can be expected if patient preferences and choices are considered.
Originality/value
This paper proposes a framework for appointment scheduling problem in outpatient departments. It is concluded that more revenue can be achieved if more choices are provided for patients to choose from and patient preferences are considered. Additionally, an appointment decision can be made timely after receiving patient preference information. Therefore, the proposed model and policies are convenient tools applicable to an outpatient department.
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H.C.W. Lau, F.T.S. Chan, Richard Fung and Christina W.Y. Wong
Attempts to introduce a quality measurement scheme (QMS) that is able to assess the immediate feedback of customers globally in real time, followed by a data mining process, which…
Abstract
Attempts to introduce a quality measurement scheme (QMS) that is able to assess the immediate feedback of customers globally in real time, followed by a data mining process, which is an interactive process that involves assembling the data into a format conducive to producing a multi‐dimensional analysis using an online analytical processing (OLAP) approach. In addition, an XML schema, which provides a universal syntax to facilitate the exchange of data, is used in the design of the QMS to support the data mining process. To validate the feasibility of QMS in real industrial situations, a case example is covered, showing promising test results based on the proposed scheme.
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Henry C.W. Lau, Peter K.H. Lau, Richard Y.K. Fung, Felix T.S. Chan and Ralph W.L. Ip
This paper attempts to propose a virtual case‐based benchmarking system (VCBS) which incorporates computational intelligence technologies into partners' benchmarking process to…
Abstract
Purpose
This paper attempts to propose a virtual case‐based benchmarking system (VCBS) which incorporates computational intelligence technologies into partners' benchmarking process to support decision‐making.
Design/methodology/approach
The proposed system consists of three main modules: data repository module, OLAP module and case‐based reasoning (CBR) module. The VCBS is a web‐based application that enables users to access the system and submit information to the system in anywhere at anytime. The database repository, on the other hand, maintains and acquires the data that are generated in the transactions processes and other workflow processes. It also ensures the entire valuable data which are accessible for the management to make decisions. The OLAP and the CBR modules are considered as the brain of the VCBS. The CBR module is aimed for short‐listing candidate, while the OLAP module is utilized for benchmarking the short‐listed candidate.
Findings
The VCBS is particularly useful in situations where multiple supply chain partners are involved to achieve the common objective to produce the products to the best satisfaction of customer demands with the lowest possible cost.
Research limitations/implications
Since data warehouse does not update in real time it only performs update periodically during non‐office hours to avoid network traffic. The solution provided to the company may not be the most updated information.
Originality/value
The proposed system improves the current practice of partner selection by adopting the computational intelligence technologies into the traditional partner selection process with the assimilation of data repository, CBR and OLAP to form the integrated system for evaluation of potential partners prior to the final decision.
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The article aims to investigate the effects of ownership and capital structure on postacquisition operating performance.
Abstract
Purpose
The article aims to investigate the effects of ownership and capital structure on postacquisition operating performance.
Design/methodology/approach
The article extends the ongoing literature from an operating loss perspective and provides empirical evidence on the probability of acquirers’ operating loss in relation to ownership and capital structure. The operating performance of publicly listed manufacturing firms in China was tracked up to five years since the completion of the mergers and acquisitions (M&A) during 2003–2014.
Findings
The empirical results show that, in a five-year postacquisition period, state-owned enterprises (SOEs) are more likely to experience operating loss than non-SOEs. The likelihood of the operating loss is negatively associated with ownership concentration, implying that concentrated ownership may serve as an effective corporate governance mechanism in the emerging economy and improve postacquisition performance. The rise in leverage increases the likelihood of postacquisition operating loss, indicating that the costs of debt may outweigh the benefits.
Originality/value
The findings contribute to the literature on ownership, debt governance and post-M&A performance from an emerging economy perspective.