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

Chang, Che‐Wei; Chen, Chung-Chih

doi:10.1016/j.cie.2010.05.008

Cited by 8 publications

(3 citation statements)

References 23 publications

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“…Bhangale et al (2004) applied TOPSIS to evaluate and rank candidate robots. Chang and Chen (2010) identified optimal performing machine using TOPSIS. Chu and Lin (2003) and Koulouriotis and Ketipi (2011) selected material handling robot using TOPSIS.…”

Section: Literature Surveymentioning

confidence: 99%

Ranking the risk categories in international projects using the TOPSIS method

Dandage

Mantha²,

Rane³

2018

IJMPB

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Purpose The purpose of this paper is to review the risk categories which are predominant in international projects and to rank them according to their effect on project success. Design/methodology/approach A literature survey of peer-reviewed journal articles, survey reports and books on project management is used as the research methodology. One among the various multi-criteria decision making methods named as Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) has been used to rank the risk categories according to their importance. The data for TOPSIS were collected through questionnaire as the research instrument. Findings The findings derived from evaluation of the publications led to the identification of eight different types of risk categories associated with international projects. The TOPSIS method resulted into political risks, technical risks and design-related risks as the top three risk categories in international projects. Contractual and legal risks and fraudulent practices-related risks are relatively low-ranked risk category. Research limitations/implications The findings will be useful in successful implementation of international projects as the knowledge of risk categories and their ranking will help project manager to plan the risk response strategies. A larger sample size for decision makers and more variety of projects can give more exhaustive risk categories and their ranking. Practical implications This paper explores eight different risk categories in international projects. It represents the ranking of risk categories according to their importance in project success. This will be helpful to project managers for developing a general framework for planning the appropriate risk response strategies. Social implications Governments of many countries around the world are encouraging their industries to undertake and successfully complete projects in foreign countries. However, many industries experience failure in projects as they fail to implement the risk management (RM) effectively in international projects. This research work provides the risk categories in international projects and their ranking which can assist in developing strategies to respond the risk appropriately. Originality/value This paper uses the TOPSIS method for ranking major types of risk categories in international projects. It might represent new opportunities for rigorous and relevant research that would contribute to an in-depth knowledge of RM methodologies.

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Section: Literature Surveymentioning

confidence: 99%

Ranking the risk categories in international projects using the TOPSIS method

Dandage

Mantha²,

Rane³

2018

IJMPB

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“…Although different MCDM exist, all of them follow a number of steps: problem definition, identification of alternatives, criteria selection, preparation of the decision matrix, and assigning weights to the criteria. MCDM are also important methods for analysing data, providing the flexibility and ability to promote the development and implementation of RE (Chang & Chen, 2010). There are a great deal of MCDM used in the analysis of energy policies (Pohekar & Ramachandran, 2004): Multi-Attribute utility; the outranking methods such as ELimination Et Choix Traduisant la Realité (ELECTRE) (Roy, 1968); and The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) (Brans, Mareschal, & Vincke, 1984); The Analytic Hierarchy Process (AHP) (Saaty, 1980); or The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Hwang & Yoon, 1981).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of suitable locations for the installation of solar thermoelectric power plants

Sánchez-Lozano

García-Cáscales

Lamata

2015

Computers & Industrial Engineering

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“…To ensure that a manufacturing process is not interrupted, a real-time IAMS is necessary [2,3]. In addition, since companies require an IAMS that is tailor-made for their operations, they must cooperate with vendors in exchanging information and technology to ensure that the software that is eventually purchased aligns with their business requirements [4,5]. The most effective collaborative technology must select for software contractors [6,7], and the most appropriate and effective approach for evaluating results.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Smart Alarm Systems for Industry 4.0 Technologies

Chang

2020

Applied Sciences

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Traditionally, the footwear industry is labor intensive, and cost control is key to ensuring shoe companies can be competitive. The development of Industry 4.0 concepts, used in high-tech industries and blockchain production information systems, enables the creation of smart factories with online alarm management systems, to improve manufacturing efficiency and reduce human resource requirements. In this paper, the performances of the causal association assessment model and the technique for order preference by similarity to the ideal solution (TOPSIS) model in evaluating large data blockchain technologies and quality online real-time early warning systems for production and raw material supplier management are compared, to increase the intelligence of production and to manage product traceability.

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

Cited by 8 publications

References 23 publications

Ranking the risk categories in international projects using the TOPSIS method

Ranking the risk categories in international projects using the TOPSIS method

Evaluation of suitable locations for the installation of solar thermoelectric power plants

Evaluation of Smart Alarm Systems for Industry 4.0 Technologies

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