Che-Wei Chang

An application of AHP and sensitivity analysis for selecting the best slicing machine

Wafer slicing is a complex manufacturing process, complicating efforts to monitor process stability and quality control effectively. This study discusses and develops a manufacturing quality yield model for forecasting 12 in. silicon wafer slicing based on the Analytic Hierarchy Process (AHP) framework. Decision Makers can select evaluation outcomes to identify the most precise machine. Additionally, EWMA control chart is presented to demonstrate and verify the feasibility and effectiveness of the proposed AHP-based algorithm. Finally, sensitivity analysis is performed to test the stability of the priority ranking. Therefore, this work illustrates how the AHP model would be implemented to help engineers determine the manufacturing process yield quickly and effectively.

Evaluating digital video recorder systems using analytic hierarchy and analytic network processes

Digital video recorder (DVR) systems are novel security products with significant potential for application in the surveillance market, which, like many other areas of security technology, is changing quickly. Consumer demand and procuring budgets of system development firms are increasingly being emphasized, motivating upgrades to system quality. Digital surveillance systems include both hardware and software. Procurers have difficulty complying with these standards due to the wide gap between the descriptions in the standards and interpretations of evaluations of digital video recorder systems such as the functions of channel, recording, playback and display, communication and remote transmission. A case study compares the analytic hierarchy process (AHP) and analytic network process (ANP) decision models, and the comparison results indicate that interdependencies can affect real decisions. For network-like decision models (i.e., decision problems that can be structured in a network model form), ANP represents an effective tool for providing an accurate solution for administrators or managers of this case.

Applying fuzzy hierarchy multiple attributes to construct an expert decision making process

The main objective of this paper is to propose an approach within the AHP framework for tackling the uncertainty and imprecision of service evaluations during pre-negotiation stages, where the experts comparison judgments are represented as fuzzy triangular numbers. A fuzzy prioritization method, which derives crisp priorities from consistent and inconsistent fuzzy comparison matrices, is described. The fuzzy analytic hierarchy process (FAHP)-based decision-making method can provide decision makers or buyer a valuable reference for evaluating software quality. A case study demonstrates the effectiveness of the proposed scheme. Importantly, the proposed scheme can assist decision makers in assessing the feasibility of digital video recorder system to management public space, making it highly applicable for academic and commercial purposes.

Using expert technology to select unstable slicing machine to control wafer slicing quality via fuzzy AHP

Silicon wafer slicing is an increasingly complex manufacturing process. This involves high purity levels, crystallographic perfection and precise mechanical tolerances, thus 12in. wafer slicing is the most difficult in terms of semiconductor manufacturing yield. As silicon wafer slicing directly impacts production costs, semiconductor manufacturers are especially concerned with increasing and maintaining the yield, as well as identifying why yields decline. The criteria for establishing the proposed algorithm are derived from literature review and modified Delphi method in semiconductor manufacturing. The main objective of this paper is to propose a new approach within the AHP framework for tackling the uncertainty and imprecision of silicon wafer slicing evaluations during manufacturing process stages, where the decision-makers comparison judgments are represented as fuzzy triangular numbers. Additionally, the proposed algorithm can select the evaluation outcomes to identify the worst machine of precision. Finally, results of EWMA control chart demonstrate the feasibility of the proposed fuzzy AHP-based algorithm in effectively selecting the evaluation outcomes and evaluating the precision of the worst performing machines. So, through collect data (the quality and quantity) to judge the result by fuzzy AHP, it will the key to help the engineer can find out the manufacturing process yield quickly effectively.

Fuzzy hierarchy sensitive with Delphi method to evaluate hospital organization performance

The conventional accreditation policy of Taiwanese hospitals involves helping promote and executing national healthcare quality policies, certifying healthcare quality, supervising the management of health care organizations, pursuing a harmonious relationship between care providers and patients, and enhancing national healthcare quality. However, the quality indicators in use by Department of Health, Executive Yuan, Taiwan (DOH) cannot indicate overall organization performance of each hospital and assess hospital operating crisis. In many cases the preference model of the human decision maker is uncertain, and it is relatively difficult for the decision maker to provide exact numerical values for the comparison ratios. This study proposal fuzzy analytic hierarchy process (FAHP) and fuzzy sensitive analysis-based approach to resolve the uncertainty and imprecision of service evaluations during pre-negotiation stages, where the comparison judgments of a decision maker are represented as fuzzy triangular numbers. A novel fuzzy prioritization method, which derives crisp priorities (criteria weights and scores of alternatives) from consistent and inconsistent fuzzy comparison matrices, is also proposed. Importantly, the proposed model can provide Taiwans hospital accreditation policy a reference material, making it highly applicable for academic and government purposes.

Integrating fuzzy theory and hierarchy concepts to evaluate software quality

This study proposes a software quality evaluation model and its computing algorithm. Existing software quality evaluation models examine multiple characteristics and are characterized by factorial fuzziness. The relevant criteria of this model are derived from the international norm ISO. The main objective of this paper is to propose a novel Analytic Hierarchy Process (AHP) approach for addressing uncertainty and imprecision in service evaluation during pre-negotiation stages, where comparative judgments of decision makers are represented as fuzzy triangular numbers. A new fuzzy prioritization method, which derives crisp priorities from consistent and inconsistent fuzzy comparison matrices, is proposed. The Fuzzy Analytic Hierarchy Process (FAHP)-based decision-making method can provide decision makers or buyers with a valuable guideline for evaluating software quality. Importantly, the proposed model can aids users and developers in assessing software quality, making it highly applicable for academic and commercial purposes.

An organisational performance measurement model based on AHP sensitivity analysis

This research proposes an Analytic Hierarchy Process (AHP) sensitivity analysis to evaluate organisational performance of hospitals. The relative weights of evaluation criteria are determined using the AHP sensitivity analysis, followed by ranking of the hospitals for decision makers to evaluate in medical-related sectors. The AHP sensitivity analysis-based decision-making method is used to construct an evaluation method, which can provide decision makers or administrators of hospital with a valuable reference for evaluating the organisational performance. Consequently, the proposed model can assist the medical sector to assess the organisational performance of hospitals, making it highly applicable for academia and commercial purposes.

Developing a Project Evaluation and Testing Model to Assess Stable Photovoltaic Slicing Machine

This study discusses and develops a project selection model for the purchase of diamond cutting machines for 12-in. photovoltaic silicon wafer slicing based on an analytical network process and preference by similarity to ideal solution (ANP-TOPSIS) method. Simultaneously, process capability indices are presented to test and verify the feasibility and effectiveness of the proposed method. The proposed method can help decision makers to establish a project evaluation and testing mode to affect and choose the best mode for diamond cutting machines of photovoltaic wafer slicing.

Group Decision–Making in a Multiple Criteria Environment—A Case Using the AHPGR Model to Assess Digital Video Recorder Systems

Digital video recorder software is increasingly common given the burgeoning popularity of the surveillance market. The proposed model includes the Analytic Hierarchy Process (AHP) to determine the weights of evaluation. Grey Relational Analysis (GRA) is then performed to rank the digital video recorder software. The AHP and GRA-based decision-making method can provide decision makers or buyers with a valuable reference for evaluating software quality. A case study demonstrates the effectiveness of the proposed scheme. Importantly, the proposed scheme can assist decision makers in assessing the feasibility of digital video recorder software, making it highly applicable for academic and commercial purposes.

Development of expert decision model to monitor precision of solar silicon wafer machine line

In this study, we develop a two-stage decision model for managing uncertainty and imprecision of solar silicon wafer slicing evaluations during a wafer manufacturing process. Stage 1 is the evaluation process, which is performed by a procedure based on a combination of the fuzzy analytic hierarchy process (AHP) and the TOPSIS method. Stage 2 is the verification process, in which process capability indices are calculated to verify the feasibility and effectiveness of the proposed methods.