Roger Jianxin Jiao

Concurrent Enterprising for Mass Customization

Enterprises in all branches of industry are becoming more customer driven. The increasing interest and effort of business practices heading towards mass customization have been witnessed by an extensive study of these approaches in both academia and industry alike. Mass customization has been recognized as a new battlefield for manufacturing enterprises. It enhances profitability through a synergy of increased customer-perceived value and cost reduction in design, manufacturing and the supply chain. Mass customization through concurrent enterprising is an approach to achieving an alliance of customers, products, processes, and logistics by means of parallelity, integration, standardization, teamwork, and many others, for delivering an increasing product variety to satisfy diverse customer needs while maintaining near mass production efficiency. It is a complex process where the concurrent engineering and extended/ virtual enterprising approaches have roles to play in coordinating various product life-cycle concerns. Though the oxymoron ‘‘mass customization’’ was coined in the mid-1980s, research has started to pick up pace only in recent years. The number of papers published on various aspects of mass customization has increased five-fold in the last decade. With this in mind, the intention of this special issue is not only to discuss the state-of-the-art of concurrent enterprising methods and approaches toward customer-driven manufacturing, but also to explore the obstacles and challenges of implementing mass customization, as well as to analyze its potentials and capabilities. Section 2 of this editorial opens the discussion by briefly introducing some fundamental issues of mass customization as key strategies for customer-driven enterprises. Section 3 summarizes the general themes highlighted by the papers included in the special issue. In Section 4, we comment on the implications of these papers for future research on mass customization systems within the general framework of concurrent enterprising. Finally, this editorial is concluded with acknowledgements to those individuals who have given us support during the process of collating the special issue.

Customer Requirement Analysis Based on an Analytical Kano Model

To facilitate effective analysis of customer requirements, the Kano model for customer satisfaction has been proposed to classify customer requirements based on survey data. However, traditional Kano is inadequate in quantitative evaluation and it lacks proper criteria for requirement classification. In this regard, this paper proposes an analytical Kano (A-Kano) model to address the key issues of customer requirement analysis. A set of Kano indices is defined to estimate customer preference based on quantitative measurements. Next, the Kano classifiers are defined as the criteria for classifying the customer requirements. The merit of the classification is evaluated against a Kano evaluator, which is a shared surplus of customer-perceived utility and the producers capability. The A-Kano model is expected to classify functional requirements into logical groups, which leads to an optimal tradeoff between customer satisfaction and producer capability.

Development of an online quality information system for e-manufacturing

Purpose – In an e‐manufacturing environment, the acquisition of real time quality data and information is paramount for distributed collaborative manufacturers to make quick and correct actions towards quality problems in a manufacturing process. This paper attempts to assist manufacturers in obtaining such data and information and further to make decisions regarding quality control.Design/methodology/approach – In this paper, an online quality information system (OQIS) for quality control in an e‐manufacturing environment is presented. The common object request broker architecture standards and client‐server technologies are applied to obtain real time data and information whenever required at different locations. In addition, several modules, responsible for product design, process planning, quality control and data input, are developed within a coherent OQIS information model.Findings – Preliminary results show advantages of the OQIS for companies to obtain real time quality data and information. It ca...

Special Issue: Platform product development for mass customization

Platform product development is a contemporary approach to agile product development for mass customization. Distinctive product variants are derived or customized from a platform that is defined as components and subsystems commonly shared across a product family. A well-organized platform is essential to connect different parties of an enterprise including soliciting customer needs through order fulfillment to field service. Hence, it is also critical to achieve the economy of scale by identifying repetitive applications of share tooling, knowledge, and other resources. In this Special Issue, we attempt to cover the different aspects of platform product development. The topics span a wider range of artificial intelligence (AI) disciplines, from knowledge representation to knowledge support systems. It identifies a fertile area not only for applying AI to contemporary issues of design and manufacturing systems but also for enriching the methodology for developing AI systems in manufacturing enterprises. Indeed, we consider that numerous successful applications in the industrial sectors highlight a future direction for productive AI applications in industry.

Citarasa driven vehicle configurator

Citarasa driven vehicle configurator is a proposed approach on building configuration rules that allow users to convert soft preferences into production specifications and furthermore to bill-of-materials. This paper presents an example of computerized configuration system that enables the process from customer engineering to design and production stages. The configuration approach is based on a combination of selective and generative rules and can be integrated with existing ERP systems.

Hospital linens inventory control re-engineering based on RFID

Cost-conscious businesses have focused on using radio frequency identification (RFID) systems to enhance the efficiency in the supply management/logistics process. RFIDpsilas application in hospital business processes is increasing rapidly and a number of safety-critical clinical applications have been prototyped. Unlike barcode systems, it is necessary to implement business process reengineering (BPR) with an innovative spirit on the fundamental processes before implementing RFID to achieve greater synergy. This paper presents a based-RFID business process reengineering framework. And then Tan Tock Seng Hospital, the second largest acute care general hospital in Singapore, is used as a case study to analyze and implement linens inventory control process reengineering.

An improved adaptive CUSUM control chart for monitoring process mean

Adaptive CUSUM (namely ACUSUM) charts have received much attention recently. It is found that, by adjusting the reference parameter k dynamically, an ACUSUM chart can achieve better performance over a range of mean shifts than the conventional CUSUM chart that is designed to have maximal detection effectiveness at a particular level of shift. This article studies a new feature of the ACUSUM chart regarding an additional charting parameter, w (the exponential of the sample mean shift in (xt - mu0)w), which is also adapted according to the on-line estimated value of the mean shift. The testing cases reveal that this new adaptive CUSUM chart outperforms the earlier ACUSUM chart to a substantial degree.

A case study of obsolete part procurement process reengineering

Obsolete part procurement has to be inevitably dealt with especially in the electronic industry. Business process reengineering (BPR) has been adopted as an effective approach which can significantly improve performance of procurement process. BPR requires that there exist a fundamental and a proven, reliable methodology, which is generally applicable and repeatable. Towards this end, this paper presents the fundamentals and methodology of procurement process reengineering based on accountabilities and activities. Subsequently, Flextron which is a low volume and high mix electronic manufacturing service provider, is used as a case study to analyze obsolete part procurement process and implement procurement process reengineering for obsolete parts.

Using computer simulation for optimal staffing: A case for the patient registration process of a hospital

BACKGROUNDnSome healthcare managers use computer simulation to assist with staffing. As staffing actions are usually slow to evolve and long term in nature, computer simulation can provide the opportunity to evaluate different alternatives at substantially lower costs with fewer risks.nnnOBJECTIVEnUsing computer simulation, this paper seeks to determine the optimal number and allocation of clerks involved in the patient registration process of a hospital.nnnMETHODSnThis paper is based on a case study conducted in a hospital and uses historical data provided by the hospital in simulating the patient registration process.nnnRESULTSnThe simulation results indicate that computer simulation can be an effective decision supporting tool in modeling the patient registration process and evaluating the effects of changes in the number and allocation of clerks in the process.nnnCONCLUSIONSnBased upon a case study applying real-world data, the results of this paper would be beneficial to those who consider utilizing computer simulation for staffing decisions.

Predicting bed requirement for a hospital using regression models

High hospital bed occupancy levels have resulted into a shortage of beds to meet increasing demand. This paper describes a bed prediction model in aiding hospital planners to anticipate bed demand so as to manage resources efficiently. Through the regression models, it was found that the number of weekly mean occupied beds is related to both the rainfall and the data on Dengue cases as provided by the Ministry of Health. The regression models performed well for predicting average class B2 and class C occupied beds in the following week. Previous week¿s mean occupied beds, emergency admissions numbers, A&E attendances and special events on the week were found to be predictors of bed occupancy in class B2 and class C wards.