International Journal of Engineering & Technology IJET-IJENS Vol:14 No:01 75 143101-5959-IJET-IJENS © February 2014 IJENS I J E N S Human System Modeling for Optimum Labor Utilization and Man-Machine Configuration Rohana Abdullah 1 , Md Nizam Abd Rahman 2 , Siti Nurhaida Khalil 3 1 Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka 2 Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia, Melaka 3 Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka email: rohana_abdullah@utem.edu.my Abstract— Manufacturing organization with increased in the organizational complexity, is facing difficulty in measuring its performance. Various factors could affect manufacturing performance such as equipment performance, material planning and human resources. In this paper, focus was given primarily on the human resource which was considered as an important factor of the simulation model development to achieve optimum utilization and ensure efficient operator allocation to the machines. Static modeling was performed to capture all the critical factors contributing to the work such as the operator activity sequence, the time value for each activity and also the machine process time for each batch of product. A dynamic model was then developed to enable quantitative analysis in the optimization of human system performance. This paper illustrates the application of different modeling approaches to demonstrate advantages gained in the process of evaluating human system performance. Index Term— Human System Modeling, Simulation Modeling, Man-machine Configuration I. INTRODUCTION The manufacturing operations have increased in complexity due to constant changes required to cater to unpredictable customer demands. Siemieniuch and Sinclair [1] stated that manufacturing is considered complex if various resources that interact with each other resulted in unpredictable organization performance. Global competitions are also putting pressures on the manufacturing companies to produce products cheaper and faster. Thus, manufacturing operations are urgently exploring methods to reduce the complexity and improve the efficiency in managing the resources. Among the factor that is becoming critical to be considered in managing manufacturing complexity is the human resource. Human resources are required to fulfill orders such as in the areas of material processing, product assembly or component manufacturing [2]. Thus, the optimum utilization of the labor should be a serious consideration in order to minimize the operating cost in manufacturing [3]. This paper explores an alternative method to model human system in order to provide the manufacturing organization with an effective decision-support tool to efficiently manage human resource in the complex manufacturing environment. The two modeling approaches used in this study are: Static Modeling – enables static spreadsheet analysis coupled with trial and error runs to experiment different sets of work activities and observing the impact of a selected decision on the operator utilization and man-machine configuration. Dynamic Modeling – enables experimentations of the critical parameters in a virtual environment such as to predict the human resource performances. Some of human resource performances that can be predicted using this method are optimum labor utilization and man-machine configuration. This paper describes the possibilities to dynamically model specifically human and machine resources to predict the behavior of the manufacturing operation performance. This technique can potentially be used as a basis of a more accurate decision support tool to efficiently assist production managers in optimizing the man-machine configuration. This paper begins with literature reviews to support the various studies done in the area of human system modeling and simulation modeling. Next, it will explain the development of the static model and also the use of dynamic model to mimic the actual production case of the back-end semiconductor manufacturing facility. II. HUMAN SYSTEM MODELING Manufacturing efficiency is highly dependent on how well resources such as equipment, human and material are being managed. Due to continuous rise in labor cost, effort has been focused on human system modeling in order to address the issues and support the manufacturing operations in the quest to achieve better competitive advantage. Model such as CIMOSA can be used to analyze key aspects of human systems using enterprise (static) and simulation (dynamic) to deploy human systematically in manufacturing [4]. In modeling human system, static model via CIMOSA modeling technique is used first to model static human system model in manufacturing plant which is later used as reference to create dynamic model i.e. simulation model to quantify human performance and efficiency values and to observe the effect of these variables on the production performance i.e. the throughput and takt time [4]. Zulch [5] on the other hand stated that there are still few studies done to simultaneously plan machine and personnel. Thus, his team developed ESPE-IP which started with a static procedure that took into consideration the personnel (both technical and operators) quantity and qualification in an operation-resource-matrix and function-equipment-matrix. These input combined with product demand and machine