Determining optimal process mean for small and medium juice processing industries using markovian model - Razali, Hazlina (2014)
The determination of process mean is important in industries especially for items that governed by laws and regulations on net content labelling. Thus, the economic selection of optimum process mean is critically significant since it will directly affect the quality characteristic of item. By assuming the quality characteristic is normally distributed, an item that undergoes the juice filling in the container can be classified as accepted product, under-filled or over-filled by the system which is successfully transform to the finishing product. This research is focused on the setting of process mean in juice processing industries, especially before production starts as it is important in order to produce an item that fulfil within the specification limit with the aim of gaining the maximum profit. Moreover the determination of optimal mean value involves a complex decisions and small and medium enterprises (SME’s) constraint is especially in financial point of view. The Markovian model is chosen as it considers the long-term probabilities in dynamic system. In this research, the analysis of selecting the process mean of juice filling in the bottle in the SME production is presented. Three main objectives are stated, namely, to propose a Markovian model for mean value estimation as a main parameter estimation of expected profit estimation, to simplify the process of selecting optimal mean value estimation in Markovian model using quartile-based method and to evaluate the performance of Markovian model using iteration rate for estimation in juice processing industries. The process of juice filling from the raw materials until end products is developed based on the single-stage process. The Markovian model that considered the under-filled and over-filled products is proposed in the study. By varying the under-filled and over-filled cost, the analysis shows the significant results of Markovian model to determine process mean which maximizes the expected profit per item. The simplification method of targeting process mean by using quartile-based is also performed in order to reduce and minimize the searching iteration process of optimal mean. The variation of juice minimum volume in the bottle is set from 1% to 10% lower than upper limit value of each bottle that available in the market. The variation is needed in order to evaluate the trends of process mean determination. The main contribution of this research is the Markovian model that is used in juice processing industries, which refer to the accepted bottles, under-filled bottles and over-filled bottles. From the different state of finished product, the determination of optimal process mean is referred to the maximum profit gained. Besides, the simplification method of searching the optimal process mean has shown a significant outcomes which reduce and minimize the iteration process. By varying the lower limit of amount in the bottle, one can see the trends of optimal process mean and yet use the variation as a guide to set the process mean before start the juice filling process.