Increasing environmental awareness and stringent environmental regulations have motivated many companies to incorporate ecodesign into product development. To assist companies to address the challenge, this research presents a design for environment (DfE) methodology to evaluate and improve derivative consumer electronic product development using a back-propagation neural network (BPNN) model and a technique for order preference by similarity to ideal solution (TOPSIS) method. Based on use of a BPNN, the life cycle assessment (LCA) models are developed to estimate quantities of hazardous chemical substances and energy consumption for a derivative consumer electronic product throughout the product life cycle. A performance evaluation and improvement model for DfE is then devised based on the TOPSIS method to analyze the ecodesign performance and provide concrete improvement strategies. With the aforementioned analysis of environmental performance, an enterprise can profoundly understand and significantly enhance the relative DfE performance of a new product compared to the similar competitive products. Finally, we apply an optical mouse development project as a case to elaborate and demonstrate the effectiveness of the proposed methodology. These analytical results can let us understand the DfE performance ranking and acquire the maximum reduced quantity of each DfE criterion for each module of a new product. Meanwhile, to enhance the green competitiveness of the new product, we recommend that the engineers should decrease the area of the circuit board of the new product. In addition, the material of the USB cable for the new product should be switched from the PVC material to the PE material.

Due to rapid changes of markets and pressures of competitions, the manufacturing companies are forced to adapt their production ways to support diversity of customer’s needs and increase of new product developments. As biological organisms are quite capable of adapting to environmental changes and stimulus, bio-inspired concepts have been recognized much suitable for adaptive manufacturing system control. This paper, therefore, proposes a novel concept of NeuroEndocrine-Inspired Manufacturing System (NEIMS). The proposed NEIMS control architecture is based on analogies with neuro-control and hormone-regulation principles. It has the capability to explicitly specify production control schemes including control points, material, information flow paths and logical operations, and to agilely deal with the frequent occurrence of unexpected disturbances at the shop floor level. From the cybernetics point of view, the control model of NEIMS indicates adaptive behavior to the changes in products demands due to external environment and malfunction of manufacturing cells as an internal environment. Finally, a prototype system has been set up to enable the NEIMS simulation.

The paper presents the application of augmented reality for aiding product design and development of machinery systems. Augmented reality technology integrates an interactive computer-generated word with an interactive real word in such a way that they appear as one environment. AR technology can enhance a user’s perception of the real world with information that is not actually part of the scene but is relevant to the user’s present activity. Presented in the AR system is a mode for changing views of data — especially 3D models — allowing the user to understand the prospective machinery system in a more comprehensive way, thus making the design process more efficient than the one supported by conventional present-day CAD systems. The presented prototype system contains an expert system integrated with AR system and allows the delivering of knowledge to the designer about successive steps of the design process of a mobile robot and practical solutions of realized constructional problems. An approach concerning AR enables the system user to analyze and verify solutions (represented as 3D models) relative to real scenes/objects. This approach is advantageous because the real environment around us often provides a vast amount of information that is difficult to duplicate in a computer. In some cases, the application of an AR system could be an optimal way to verify developed products.

Footwear have been evaluated mostly using commercially available products, while some researchers have used custom shoes. Hence, the understanding of the effects of various parameters of a shoe is quite limited. The footbed simulator invented in recent years allows a range of parameters to be studied in quiet standing. It can be used to evaluate perceived feel and center of pressure changes to changes in heel height, seat length, material, wedge angle and toe spring. This paper is meant to show the value of the footbed simulator in terms of research and the actual production of shoes. A study performed with two heel heights, three combinations of seat length and material and three wedge angles showed that the perceived feel is closely related to the center of pressure. The results also show the optimum footbed has a significantly different perceived feel. Thus, the footbed simulator is an ideal way to generate custom footwear designs.

The outage of a transformer in a power generation system will generally result in a shutdown of the entire system. Consequentially, large amounts of revenue are lost to the plant owner with a substantial negative impact on the civil community and industrial customers. This paper analyzes the current maintenance practices (i.e., an as-is process model) of a transformer manufacturing company, which provides maintenance services to power generation plants and reports the major weaknesses in current business practices. The maintenance weaknesses include isolated processes and paper based information communication. These inefficient processes result in service delays, cost increases, and inappropriate responses to customers’ specific requests and complaints. To improve the efficiency and flexibility of the entire transformer maintenance service system, an e-integration approach is implemented with three key tasks. First, the current business processes are re-engineered to provide an improved (to-be) business model. Then, we replace paper based documentation methods with an electronic filing system for efficient and cost-effective information exchange. Afterward, the improved process model is implemented as an Internet based system to enhance the interactions among the transformer manufacturer, end-users, and service contractors for customized maintenance services. The case study demonstrates that implementing the e-integration approach increases the efficiency and effectiveness of the customized maintenance services.

In recent years, e-learning system has been adopted as a training tool in many firms, as it can help employees to complete training in a short time and at a low cost. Within this context, since 2003 the Industrial Development Bureau (IDB) of the Ministry of Economic Affairs (MOEA) in Taiwan sponsored more than 50 enterprises each year to help them implement customized e-learning systems. Past research on e-learning mostly focused on one criterion and adopted regression approach, such as examining the relationships between satisfaction or continued usage intentions and various antecedent factors. Although the regression method could uncover the significant factors of e-learning adoption, they can not show the can (weighting) of each factor, and thus firms cannot allocate the optimal levels of resources. To overcome this problem, this study collected factors related to firms implementing customized e-learning systems from a review of the literature and expert opinions, and then constructed a hierarchical factor table. Based on the appropriateness and independence of factors, and as assessed by experts in the project promotion office of the IDB, e-learning solution providers and project leaders of the IDB sponsored enterprises, this paper then designed an Analytical Hierarchy Process (AHP) format questionnaire and sent it to these same experts to gather their responses. The factor weightings were derived based on the Fuzzy Analytic Hierarchy Process (FAHP) method. Finally, analysis of key factors was performed and recommendations provided. Based on the results for this work, service industry firms with limited resources can achieve proper resource allocation and more quickly and successfully adopt customized e-Learning systems.

This study utilizes fuzzy analytic hierarchy process (FAHP) to analyze decision-making patterns with regard to third-generation wireless communications (3GWC) service adoption, and to provide customized strategic recommendations to suppliers of 3GWC services regarding marketing and resource allocation in the context of the Chinese 3GWC market. First of all, a three-layer hierarchy of 3GWC adoption factors is developed by referring to the relevant literature and industry reports. A questionnaire of pairwise comparisons in the fuzzy AHP format is then designed and distributed to experts familiar with the handset market in Shanghai, China. These surveys are then analyzed using fuzzy AHP to establish an understanding of the weights and impacts of the various factors. The results show that the four most important factors for the adoption of 3GWC systems are: (i) handset price and voice and data-transmission fees; (ii) handset aesthetics; (iii) personalization; and (iv) network coverage. These findings suggest that providers of such services should customize and diversify the content/applications they offer and ensure the speed and reliability of network access. In addition, handset designs should be in accordance with consumer demands. If these steps can be achieved, then consumers will adopt 3GWC services more rapidly.