Research On The Identification And Prediction Of Production Logistics Bottleneck Considering The Delay Penalty Cost

Production logistics bottleneck is the key of the production logistics optimization, but bottleneck is changing constantly because the production logistics is dynamic and complicated, so the identification and prediction of production logistics bottleneck is especially important. Aiming at the semi-finished production logistics problem in the production logistics, the bottleneck identification and prediction research is put forward, the main contents include:1. The identification research of production logistics bottleneck based on the delay penalty cost. According to the delay problem in the semi-finished production logistics, the bottleneck identification based on delay penalty cost was proposed. The maximum delay penalty cost was defined as the production logistics bottleneck. Delay penalty cost function consisted of the delay time and times, and a bottleneck model was established as this objective function. An order-component-process three layer traversal algorithm was designed to solve the two variables of the delay time and times in the model. Through the example, the effectiveness and rationality of the bottleneck identification method was illustrated.2. The prediction research of production logistics bottleneck based on the bottleneck index. The bottleneck identification based on the delay penalty cost belonged to later identification. To solve this problem, the production logistics bottleneck prediction based on bottleneck index was proposed. This contents included three parts:(1) The factor analysis of the bottleneck. From the analysis of the production delay, the effective capacity load ratio was determined to be the production logistics bottleneck attributes. From the Overall Equipment Effectiveness and Work-in-Process inventory, the loss of productivity was quantitatively descripted. And the more detailed qualitative analysis was proposed.(2) The bottleneck prediction model. According to the effective capacity, the bottleneck index concept was put forward to establish a prediction model. The bottleneck index and bottleneck sensitivity index was proposed to analyze the transfer tendency and its sensitivity affected by factors.(3) The bottleneck factor prediction model. On the detailed introduction of the neural network theory, the model of the bottleneck factor prediction was constructed. In the example of using the MATLAB, the effectiveness of the method was verified.