Integrated economic design of quality control and maintenance management: Implications for managing manufacturing process

Rajesh Saha (), Abdullahil Azeem (), Kazi Wahadul Hasan (), Syed Mithun Ali () and Sanjoy Kumar Paul ()
Additional contact information
Rajesh Saha: Bangladesh University of Engineering and Technology
Abdullahil Azeem: Bangladesh University of Engineering and Technology
Kazi Wahadul Hasan: Bangladesh University of Engineering and Technology
Syed Mithun Ali: Bangladesh University of Engineering and Technology
Sanjoy Kumar Paul: University of Technology Sydney

International Journal of System Assurance Engineering and Management, 2021, vol. 12, issue 2, No 5, 263-280

Abstract: Abstract This paper develops an integrated economic model for the joint optimization of quality control parameters and a preventive maintenance policy using the cumulative sum (CUSUM) control chart and variable sampling interval fixed time sampling policy. To determine the in-control and out-of-control cost for both mean and variance, a Taguchi quadratic loss function and modified linear loss function are used, respectively. Imperfect preventive maintenance and minimal corrective maintenance policies were considered in developing the model, which determines the optimal values for significant process parameters to minimize the total expected cost per unit of time. A numerical example is used to test the model, which is followed by a sensitivity analysis. The integration of CUSUM mean and variance charts with the maintenance actions are proven successful to detect the slightest shift of the process. The findings reveal that among all the cost components, process failure due to external causes and equipment breakdown has a noteworthy attribute to the total costs of the optimized model. It is expected that top managers can utilize the suggested combined model to minimize the costs related to quality loss and maintenance policy and achieve economical advantages as well.

Keywords: CUSUM control chart; VSIFT sampling policy; Quality control; Maintenance policy; Average run length; Genetic algorithm (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s13198-021-01053-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:12:y:2021:i:2:d:10.1007_s13198-021-01053-7

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-021-01053-7

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().