Dah-Chuan Gong

AN INTEGRATED PRODUCTION-INVENTORY MODEL FOR DETERIORATING PRODUCTION WITH DEFECTIVE ITEM REWORK AND JOINT MATERIAL REPLENISHMENT POLICY

ABSTRACT This paper considers an integrated production-inventory model which determines an optimal production cycle time and economic joint replenishment quantity of raw materials in a batch production system. The production process is assumed to be imperfect, and thus certain amount of item produced become defective. The defective items are assumed to be reworked immediately after the regular production ends and rework efforts are assumed to be performed under perfect condition. The objective is to minimize the expected total cost for the system over an infinite horizon. An algorithm to obtain an optimal or near optimal solution is presented. To demonstrate the models fidelity, a numerical example is provided to illustrate the model. Sensitivity analysis is also performed and discussed. This deterministic model attempts to provide mangers with guidelines to evaluate the proper production cycle time and the purchase quantity of raw materials of an imperfect production process simultaneously under defective item rework and joint material replenishment policy.

Agent-based knowledge management system with APQP: implementation of semiconductor manufacturing services industry

Future challenges posed to semiconductor manufacturing services firms demands a system framework which could not only introduce, development, and design new products into mass production with customer-acceptable quality level and profitable approaches, but also re-use best practice in the shop floor to continuously optimise the existing order fulfilment process with effectiveness and efficiency. Advanced product quality planning (APQP) tool integrated with agent-based knowledge management (KM) intelligence develops a systematic framework that responds to such challenges. We propose an APQP tool working with an agent-based knowledge management system (ABKMS) which builds on organisational knowledge resources and works with the APQP concept as well as KM agents. The proposed framework reflects how an APQP tool with KM agents seeks significant inroads into process knowledge repository to recommend a solution for decision making in delivering semiconductor manufacturing services in customer selection, parts and material selection, bill of material, equipments, and tools selection, with a modified APQP concept to work out the approach to be used to develop the streamlined and common process.

On a Production-Inventory Model for Deteriorating Items Subject to an Imperfect Process

ABSTRACT This paper considers a production-inventory model for deteriorating items subject to an imperfect production process. A product is to be manufactured in cycles on a system that is assumed to be in an in-control state at the beginning of a production run. The demand rate of the product is assumed to be fairly stable and known. For each production cycle, the production is run for a predetermined amount of time during which items produced are used to meet the demand and to build inventories. Items produced in this state are subject to a constant rate of deterioration. After a production run is completed, the system will be kept idle until all on-hand inventories are depleted. Since no shortages are allowed, a new production run will begin only when the inventory level reaches to zero. During a production run, the production system may shift at random from an in-control state to an out-of-control state. Subsequently, items produced in the out-of-control state are subject to a higher deterioration rate than those units produced during the in-control state. The objective of the model is to determine a production uptime so as to minimize the expected total cost per unit time including the setup, the inventory holding, and the deterioration cost. The time-to-shift of the productions system and the time-to-deterioration of an item are assumed to be exponentially distributed. A closed-form solution of a near optimal production uptime is derived.

DESIGN OF AN INTEGRATED MAINTENANCE MANAGEMENT SYSTEM

ABSTRACT This research addresses the overall view of an Integrated Maintenance Management System (IMMS). Its structure consists of three subsystems of the Real Time Monitoring (RTM), Reliability Centered Maintenance (RCM), and the Computerized Maintenance Management System (CMMS). These subsystems are not independent. A stand-alone RTM cannot continuously provide improving suggestions without analytical capability. On the other hand, a RCM may offer ambiguous analyses if it is short of real-time data from equipment. In addition, a tedious CMMS creates the burden for making decisions. Therefore, these three subsystems should be considered together to form an integrated structure. This structure is expected to provide guidance for the maintenance operation flow development of an efficient factory. Modules of the IMMS will be illustrated in details. A mold injection machine is also described in this paper for the argument.

RESEARCH ON THE E-BUSINESS ENVIRONMENTAL FACTORS FOR TAIWAN ELECTRONIC ENTERPRISE CONCERNING TAIWAN AND CHINA

ABSTRACT Whether or not E-Business can be successful depends on the environment factors, which is very important for E-Business. The purpose of this research is to compare the differences between Taiwan and Chinas E-Business from the perspective of Taiwanese electronic enterprises. This research is mainly to offer the environmental information to Taiwanese businessmen, in order to promote E-Business and to serve as the reference point for Taiwan government to access the E-Business field.

An efficient job-releasing strategy for semiconductor turnkey factory

The semiconductor integrated circuit (IC) industry in Taiwan plays a significant role in the world, and accounts for a major market share of packaging and testing. Past studies have discussed job-releasing models for upstream IC manufacturing industries, but only few have discussed from an IC turnkey perspective for IC testing and assembly processes. This article proposes a job-releasing strategy for an IC turnkey factory that achieves the following objectives under limited resources: (1) increasing the overall equipment efficiency of IC test equipments, (2) reducing IC fabrication cycle time and (3) increasing on-time delivery rate. To balance capacity utilisation between IC assembly and testing operations, this study uses a genetic algorithm with workload regulation heuristics to find a good job-releasing plan. The proposed strategy is implemented in an IC turnkey factory and is found to outperform the conventional strategy.

Efficient job-release plan development for semiconductor assembly and testing in GA

Taiwans semiconductor integrated circuit (IC) industry plays an important role in the world and has maintained a major market share, especially, in the business of ICs packaging and testing. In the past, many studies have discussed job-release models for upstream IC manufacturing, but few emphasize on the IC turnkey factory, which including IC assembly and testing operations. In this paper, a job-release strategy for an IC turnkey factory with known assembly cycle time will be proposed. Concerning objectives under limited-capacity resources are (1) increasing the overall equipment efficiency (OEE) of IC test equipments, (2) reducing the fabrication cycle time, and (3) increasing the on-time delivery (OTD) rate. A genetic algorithm (GA) is applied to obtain an efficient job-release plan based on the data of an IC turnkey factory in Taiwan.

A comparison of RoHS risk assessment using the Logistic Regression Model and Artificial Neural Network Model

Under the RoHS Directive enacted in the European Union, there exist a number of green quality uncertainties and risks at various stages during product lifecycle management. The green product management system designed in this study, consisting of green design management, supplier management and green production management, is mainly in charge of controlling quality uncertainties and risks to prevent from producing non-green products at various stages. There is a great deal of uncertainties associated with the introduction of green quality control at every stage, and risks will rise correspondingly, thereby causing goodwill and cost losses. Consequently, green quality should be controlled in advance. To assess the extent and severity of the impact of the risk on enterprises, to focus on risk factors with strong impacts based on the priority of risk control, and to reduce the probability of risk, this study uses two approaches — Artificial Neural Network Model and Logistic Regression Model — to integrate green quality control information flow among green design management, supplier management and green production management.

A knowledge-based systems engineering approach for confirming emergent strategy-making quality

Systems engineering is an interdisciplinary engineering management approach that evolves and verifies an integrated set of system solutions to satisfy mission objectives in many areas. But literatures less focused the approach to confirm a strategic consistency and quality on enterprise strategy for engineering background managers. Hence, we explore strategy formulation process from organization hierarchy view through systems engineering methods while emergent strategy is being developed. The whole practice experiences would be extended for shared at knowledge management platform in their organization. Finally, we use an example illustrate strategic quality with a stage-gate analyzer through the above method and focus process reengineering on the ongoing NPD process. We believe that a strong linkage would be well constructed between strategy-makers and executors to improve their great foresight toward a business goal.