Application of fuzzy risk analysis for selecting critical processes in implementation of SPC with a case study
- Authors: Khorshidi, Hadi , Gunawan, Indra , Nikfalazar, Sanaz
- Date: 2016
- Type: Text , Journal article
- Relation: Group Decision and Negotiation Vol. 25, no. 1 (2016), p. 203-220
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- Description: Fuzzy risk analysis is widely used in risk assessment of components by linguistic terms. Fuzzy numbers are used to quantify the associated uncertainty. This study employs fuzzy risk analysis to evaluate processes for implementing statistical process control (SPC) in a specified manufacturing system. To reach this goal, fuzzy risk analysis has been applied based on both ranking and similarity of generalized trapezoidal fuzzy numbers in a stepwise procedure. Therefore, a new approach has been introduced for fuzzy risk analysis of processes to overcome the shortcomings of previous fuzzy risk analysis approaches. As a result, fuzzy risk analysis is used as a decision making technique to select critical processes under uncertainty. Also, the application of the proposed SPC implementation algorithm is illustrated in the manufacturing line of a car battery factory. © 2015, Springer Science+Business Media Dordrecht.
Statistical process control application on service quality using SERVQUAL and QFD with a case study in trains' services
- Authors: Khorshidi, Hadi , Nikfalazar, Sanaz , Gunawan, Indra
- Date: 2016
- Type: Text , Journal article
- Relation: TQM Journal Vol. 28, no. 2 (2016), p. 195-215
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- Description: Purpose - The purpose of this paper is to implement statistical process control (SPC) in service quality using three-level SERVQUAL, quality function deployment (QFD) and internal measure. Design/methodology/approach - The SERVQUAL questionnaire is developed according to internal services of train. Also, it is verified by reliability scale and factor analysis. QFD method is employed for translating SERVQUAL dimensions' importance weights which are derived from Analytic Hierarchy Process into internal measures. Furthermore, the limits of the Zone of Tolerance are used to determine service quality specification limits based on normal distribution characteristics. Control charts and process capability indices are used to control service processes. Findings - SPC is used for service quality through a structured framework. Also, an adapted SERVQUAL questionnaire is created for measuring quality of train's internal services. In the case study, it is shown that reliability is the most important dimension in internal services of train for the passengers. Also, the service process is not capable to perform in acceptable level. Research limitations/implications - The proposed algorithm is practically applied to control the quality of a train's services. Internal measure is improved for continuous data collection and process monitoring. Also, it provides an opportunity to apply SPC on intangible attributes of the services. In the other word, SPC is used to control the qualitative specifications of the service processes which have been measured by SERVQUAL. Originality/value - Since SPC is usually used for manufacturing processes, this paper develops a model to use SPC in services in presence of qualitative criteria. To reach this goal, this model combines SERVQUAL, QFD, normal probability distribution, control charts, and process capability. In addition, it is a novel research on internal services of train with regard to service quality evaluation and process control. © 2016 Emerald Group Publishing Limited.
An investigation on imperialist competitive algorithm for solving reliability-redundancy allocation problems
- Authors: Khorshidi, Hadi , Gunawan, Indra , Sutrisno, Agung , Nikfalazar, Sanaz
- Date: 2015
- Type: Text , Conference paper
- Relation: 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM); Singapore, Singapore; 6th-9th December 2015 p. 1041-1045
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- Description: Reliability-redundancy allocation problems (RRAPs) are optimization models that try to find the optimal number of redundant components and their reliability levels simultaneously. Many studies have been developed to solve RRAPs in recent years. There are some specific RRAP models for various system structures to maximize system reliability subject to cost, volume and weight constraints. Different meta-heuristic algorithms have been used in order to reach the best objective function value. In this study, an investigation is done on imperialist competitive algorithm (ICA) to maximize models for series and bridge systems. ICA is used by adjusting different values to algorithm's parameters. This investigation recognizes which combination is the most suitable for solving the RRAPs by ICA. Each combination has been run for 35 times. Therefore, the combinations are compared by descriptive statistics' measures and analysis of variance (ANOVA). Furthermore, the best obtained solution is compared with the previous studies.