Monitoring production time and cost performance by combining earned value analysis and adaptive fuzzy control. (January 2019)

• Record Type: Journal Article
• Authors: Zohoori, Bahareh; Verbraeck, Alexander; Bagherpour, Morteza; Khakdaman, Masoud
• Is Part Of: Computers & industrial engineering. Volume 127(2019)
• Page Start: 805
• Page End: 821
• Publication Date: 2019-01
• Subjects: Production cost and time performance -- Production monitoring systems -- Earned value analysis -- Adaptive fuzzy control -- Gain scheduling fuzzy control; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.11.019
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A real-time and adaptive production performance monitoring technique is developed. The model ensures on-time and on-budget delivery of the product to the customer. We integrate earned value analysis and gain scheduling fuzzy control. The model can absorb uncertainties and adapt with different conditions of production. The research represents the application of project management methods in manufacturing. Abstract: This paper presents a new method for measuring and improving production time and cost performance by applying project management concepts and methods. In the context of production and manufacturing industries, we demonstrate how to improve production performance by considering production as a project with limited time and budget in order to track the production progress at any given point of time. The proposed approach is capable of monitoring cost and time of production implementation in an adaptive and real-time fashion. According to the fact that in the production and manufacturing environment, cost and time of fulfilling customer demand can be considered as a measure of production performance, this research applied Earned Value Analysis from project management and integrated it with Gain Scheduling Fuzzy Control to design an adaptive monitoring system to support real-time control of production cost and time. Gain Scheduling Fuzzy Control was used to adapt the monitoring system with different conditions of the production environment. To the best of authors' knowledge, this research is a new application of Fuzzy Adaptive Control in the literature of production and project cost-time performance monitoring. The proposed model in this paper is capable of online monitoring of cost and time performance for different products, at different production periods, and machine centers. The proposed method was implemented successfully in a case study. The results indicated a substantial improvement in production time and cost performance.