Evaluation of employees with multiple skills and optimization of multi-line employee allocation problem

Employee allocation is one of the most important decision that can achieve productivity gains in a labor-intensive manufacturing system. Labor-intensive manufacturing systems usually consist of small, simple and inexpensive machines and equipments. The employee involvement in labor-intensive manufacturing line is greater than in machine-intensive manufacturing lines and indeed employee allocation directly affects the output rate of the line. Literature focusing on the employee allocation problem does not consider the difference in operation skill requirement, which is often a constraint for practical applications. The quality of employee allocation decision is largely depending on experiences, qualifications, job orientation, performance, personal characteristics of the allocated employee. The proposed approach which is motivated by this strong relationship between performance of employees and the final allocation decision has three phases; first phase is weightining the employee evaluation criteria by using Fuzzy AHP, second phase is evaluating of the multi-skilled employees based on both qualitative and quantitative criteria and determining the categories by using a combination of the alpha cut analysis and a non-parametric statistical test_Kruskal Wallis, third phase is determining the optimal solution of the multi-line employee allocation problem by formulating the linearized nonlinear MIP model. The optimization problem of finding an allocation of workers to the line minimizes the multiplication of staffing and skill levels and determines the minimum number of workers which satisfies the monthly demand. An actual application in an Turkish Defense Industry firm is also represented to prove the practicality of the method in reality. In application, all processing times and demands are deterministic and in an manufacturing line there is only one kind of product, but for a product lot-splitting is allowed.Key Words : Employee Evaluation, Employee Allocation, Multiple Criteria Desicion Making, Fuzzy AHP, Alpha Cut Method, Mixed Integer Programming