Project risk management decision-making method for manufacturing system using statistical approaches

Manufacturing systems help in planning, controlling and monitoring throughout the manufacturing processes. Failure to perform reliable systems may cause problems through its lifecycle. Specifically, risk management is particularly pertinent for manufacturing projects, thus distinctive methods and education have been developed for such risk management. Fewer attempts have been undertaken in dealing with lean production risks during constructing of projects. On the other hand, lack of methodology in recognizing and minimizing lean production risks during developing manufacturing systems resulted in nothing, except wasting a lot of money and energy, dismissing of personnel, getting loans or bankruptcy. Consequently, for a more desirable management of risks associated with mass production of a manufacturing system, it seems necessary to develop an expanded image and a perspective of future horizons when constructing a manufacturing system. In this study, a review from the previous works were conducted on risk management, particularly risks in the decisionmaking method for scheduling and line of balance monitoring in manufacturing systems. In first hand, a questionnaire based survey approaches for risks identifying and analysing of the critical risk factors were developed and presented. The survey was adopted based on the previous researches and slightly altered, pre-tested and weighted for the validity and reliability. Three keys risk elements were adopted which are; organizational scope, business strategy risk and operational risk, with 82 specified questionnaires were considered in this study. Likert scales weighed as 1 to 5 were assessed by the correspondents. The collected survey were then has been analyse using SPSS. Results showed that the risk elements from the operational risk a highly influences to the overall outcomes of the organizations. A suggestion of a conceptual model and the identification of the effective production factors was then has been discussed. Finally, a manufacturing software was developed. A validation test was successfully conducted without any error occurred. The developed software managed to perform a recommended values based on risks and will help in the success of the manufacturing scheduling.

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