Statistical Evaluation of Semi-Analytical, Analytical, and Numerical Models of the Serial Production Lines

Production lines are the backbone of the manufacturing industry. To gain the best profit out of a line it is necessary to design each line using the production system engineering. Therefore, three approaches can be used, the numerical, the analytical, and the semi-analytical approach. The aggregation method, finite state method, and the numerical approach are statistically compared concerning the analytical approach using the STATISTICA software. We analyzed the interaction between the input data and the output data for the finite state method in an illustrative example, using a full factorial design and the Design Expert software

Modeling and Dynamic Assignment of the Adaptive Buffer Spaces in Serial Production Lines

In production systems, the buffer capacities have usually been assumed to be fixed during normal operations. Inspired by the observations from the real industrial operations, a novel concept of Adaptive Buffer Space (ABS) is proposed in this paper. The ABS is a type of equipment, such as movable racks or mobile robots with racks, which can be used to provide extra storage space for a production line to temporarily increase certain buffers’ capacities in a real-time fashion. A good strategy to assign and reassign the ABS can significantly improve real-time production throughput. In order to model the production systems with changing buffer capacities, a data-driven model is developed to incorporate the impact of buffer capacity variation in system dynamics. Based on the model, a real-time ABS assignment strategy is developed by analyzing real-time buffer levels and machine status. The strategy is demonstrated to be effective in improving the system throughput. An approximate dynamic programming algorithm, referred to as ABS-ADP, is developed to obtain the optimal ABS assignment policy based on the strategy. Traditional ADP algorithms often initialize the state values with zeros or random numbers. In this paper, a knowledge-guided value function initialization method is proposed in ABS-ADP algorithm to expedite the convergence, which saves up to 80% computation time in the case study.

A Finite State Method in the Performance Evaluation of the Bernoulli Serial Production Lines

Research on the performance measure evaluation of Bernoulli serial production lines is presented in this paper. Important aspects of the modeling and analysis using transition systems within the Markovian framework are addressed, including analytical and approximation methods. The “dimensionality curse” problems of the large scale and dense transition systems in the production system engineering field are pointed out as one of the main research and development obstacles. In that respect, a new analytically-based finite state method is presented based on the proportionality property of the stationary probability distribution across the systems’ state space. Simple and differentiable expressions for the performance measures including the production rate, the work-in-process, and the probabilities of machine blockage and starvation are formulated. A finite state method’s accuracy and applicability are successfully validated by comparing the obtained results against the rigorous analytical solution.