A Brief Note On The Industrial Engineering Of A Motorcycle Carburettor Manufacturer By Predicting Customer Demand Through Forecasting Activities

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II. Career Episodes
2.1 Career Episode 1
2.1.1 Introduction. In this career episode, I describe an industrial engineering task which I undertook as part of my educational program in the bachelor degree program in Industrial Engineering department, Faculty of Engineering, Andalas University, Indonesia, during 1998-2003. In this task, I worked with my team to solve industrial engineering problems within a motorcycle carburettor manufacturer by predicting customer demand through forecasting activities, for later, was used to develop the aggregate production plan, master production schedule, rough capacity planning materials and capacity planning.
2.1.2 Background. As part of management decision, production planning can be defined as the
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Moreover, production planning and control is useful to meet demand in order to obtain the maximum profit. In this task, I lead my team to conduct forecasting of customers demand for one year period and to develop an aggregate planning, master production schedule (MPS), rough cut capacity planning (RCCP), material requirement planning (MRP) and capacity requirement planning (CRP). These activities are part of the effective and integrated manufacturing planning and control processes which is known as MRP II (Manufacturing Resource Planning), the predecessor of enterprise resource planning (ERP). The relationship of these processes can be seen in Figure 1. Our project was related to processes of top management planning and operation management execution in this figure.
2.1.3 Personal Engineering Activity Forecasting. Forecasting is the first important activity to determine production schedule in the future. It was done by predicting the future customer demand for a certain product or several products which later will become the target for production based on analysis of historical data. There are several phases for conducting quantitative forecasting, including: 1) Plotting the historical data [there are some possibility of data plotting: constant, linear, seasonal, cyclical and random] 2) Choosing several forecasting methods which is
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