Abstract
Article history: Received July 28, 2013 Received in revised format 22 October 2013 Accepted 28 October 2013 Available online December 18 2013 This paper presents an implementation of system dynamics model to determine appropriate product mix by considering various factors such as labor, materials, overhead, etc. for an Iranian producer of cosmetic and sanitary products. The proposed model of this paper considers three hypotheses including the relationship between product mix and profitability, optimum production capacity and having minimum amount of storage to take advantage of low cost production. The implementation of system dynamics on VENSIM software package has confirmed all three hypotheses of the survey and suggested that in order to reach better mix product, it is necessary to reach optimum production planning, take advantage of all available production capacities and use inventory management techniques.
Highlights
Aggregate analysis in manufacturing system design has been a popular method to detect the links between the non-feasible alternatives at earlier stages and there are various studies associated with the implementation of such method (Clark et al, 1995; Helo, 2000; Ovalle & Marquez, 2003). Stave (2002), for instance, applied system dynamics (SD) to improve public participation in environmental decisions
Kamath and Roy (2007) proposed a SD technique for detecting critical information flows based on the system dynamics model of a two-echelon supply chain
This paper presents a system dynamics model to determine appropriate product mix by considering various factors such as labor, materials, overhead, etc
Summary
Aggregate analysis in manufacturing system design has been a popular method to detect the links between the non-feasible alternatives at earlier stages and there are various studies associated with the implementation of such method (Clark et al, 1995; Helo, 2000; Ovalle & Marquez, 2003). Stave (2002), for instance, applied system dynamics (SD) to improve public participation in environmental decisions. Despite substantial amount of investment, the mill was losing money, contrary to expectations They drew on established strategic frameworks, using SD to integrate the data created by traditional analyses and developed a representation of management's collective mental model, demonstrating the feedback processes they believed would lead to success in the specialty market. They developed a dynamic hypothesis, explicated in the form of causal loop diagrams, to describe the failure of the firm's strategy to yield profitable operation for the mill. These side effect feedbacks undercut the intended impact of the new strategy
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
