Maximization of Delivery-Based Customer Satisfaction Considering Customer-Job Relationships in a Cellular Manufacturing Environment

Maximization of Delivery-Based Customer Satisfaction Considering Customer-Job Relationships in a Cellular Manufacturing Environment

Gürsel A. Süer, Aslıcan Arınsoy
Copyright: © 2014 |Pages: 20
DOI: 10.4018/978-1-4666-5039-8.ch003
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Abstract

In this chapter, the authors propose a mathematical model to maximize overall customer satisfaction subject to minimum satisfaction levels for selected customers. The mathematical model performs cell loading (i.e., assigns jobs to cells). The customer satisfaction is measured in terms of ratio of jobs completed to the total number of jobs from a customer. The proposed model connects jobs to customers. An experimentation was performed with this model in a multi-period rolling environment that tested four different fuzzy rules. Fuzzy rules were used to modify the minimum satisfaction levels for customers in a dynamic fashion in a rolling horizon. Fuzzy rules identify customers with low satisfaction in recent periods and attempt to increase their satisfaction in the following period. The performance of fuzzy rules is compared.
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Background

Demand management is the crucial linkage between marketplace and manufacturing. Some basic demand management operations are forecasting demand, specifying product requirements, setting due dates, updating customer order status and defining the requirements for manufacturing (Vollmann et al., 2005). Well-defined demand management utilizes the resources of the company, increases a company’s profit and strengthens the relationship between the company and the marketplace. In order to obtain efficient demand management, a company’s strategy, customers’ expectation and manufacturing capabilities should support each other (Vollmann et al., 2005). In this study, we consider a cellular manufacturing company that follows Make-to-Order strategy and therefore meeting customer due dates is critical to maximize customer satisfaction. Make-to-Order strategy is also critical in reducing the finished goods inventory levels as the company does not have to produce based on the forecast. Any forecast errors may lead to increased and in some cases obsolete inventory. Inventory reduction is one of desirable outcomes that can be obtained in Lean Manufacturing systems.

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