A classification and review of timed Markov models of manufacturing systems

Data-driven modeling and real-time distributed control for energy efficient manufacturing systems

In manufacturing systems with large variety of products, small- to medium-size production runs are typically carried out according to the customers’ orders. When the volume of a production run is small, the production system operates partially (or entirely) in the transient regime and the traditional steady-state analysis may become inapplicable. In this paper, under the framework of serial production lines with finite buffers and with machines having the Bernoulli reliability model, we study the problems of performance evaluation, system-theoretic properties, and bottleneck of such systems. Specifically, we study the mathematical model for the one- and two-machine cases and derive analytical formulas to evaluate the performance measures of such systems. Then, for longer lines, a computationally efficient algorithm based on aggregation is developed to approximate the system performance measures with high accuracy. In addition, the monotonicity and reversibility properties and completion time bottleneck are discussed. Finally, a case study in a lighting equipment assembly plant is described to illustrate the theoretical results obtained.

Finite Production Run-Based Serial Lines With Bernoulli Machines: Performance Analysis, Bottleneck, and Case Study

Serial lines and assembly systems are two of the most fundamental production system structures used in practical manufacturing environments. While serial lines have been studied extensively in production systems literature and practice, assembly systems have received much less attention. Among existing results on assembly systems, most are focused on steady state performance evaluation, system properties, and improvement. On the other hand, transient behavior of such systems remains largely unexplored. In the framework of assembly systems with Bernoulli machines and finite buffers, this paper develops a mathematical model for transient analysis and derives closed-form formulas to calculate the real-time production rate, consumption rates, work-in-process, and probabilities of machine starvation and blockage, during transients. Then, an improved computationally efficient algorithm for transient performance evaluation in Bernoulli serial lines is proposed. Based on the improved algorithm, an effective and efficient method for transient performance evaluation in Bernoulli assembly systems is derived. Finally, the method is extended to complex assembly system structures.

Performance Analysis of Assembly Systems With Bernoulli Machines and Finite Buffers During Transients

Advanced manufacturing systems are characterized by their complex dynamics, which are subject to constant changes caused by technology insertion, engineering modification, as well as disruption events. To support daily operation, distributed sensors are utilized to monitor the status of each process. The advantages of the sensor data are not fully realized in current production system analysis due to a lack of data-driven system level modeling. Motivated by this need, we propose a data-driven manufacturing system model to describe production dynamics and develop a systematic method to identify the causes of permanent production loss. This research enables real-time production system performance diagnosis, which is invaluable in increasing system responsiveness and improving real-time production control to effectively enhance overall system efficiency.

Production System Performance Identification Using Sensor Data

A production system is characterized by both its steady state and transient properties. While extensive research efforts have been spent in the analysis of the steady state of production systems, very few results, especially analytical ones, have been reported regarding their transient behavior. Indeed, transient behavior of production systems has significant practical and theoretical implications. A better understanding of the transient properties of production systems is critical to effective utilization of real-time production data for efficient factory floor operation and management. In the framework of serial production lines with geometric machines and finite buffers, this paper develops mathematical models for transient analysis and derives closed-form expressions for evaluating the production rate, consumption rate, work-in-process, and probabilities of machine starvation and blockage, during transients. In addition, a computationally efficient algorithm based on aggregation is developed to approximate the transient performance measures with high accuracy. Numerical experiments show that the methods developed can be applied to systems with time-varying machine parameters as well.

Guorong Chen

Papers

Transient Performance Analysis of Serial Production Lines With Geometric Machines