Throughput analysis is important for the design, operation and management of production systems. A substantial amount of research has been devoted to developing analytical methods to estimate the throughput of production systems with unreliable machines and finite buffers. In this paper we summarise the recent studies in this area. In addition to the performance evaluation of serial lines, approximation methods for more complex systems, such as assembly/disassembly systems, parallel lines, split and merge, closed-loop systems, etc., are discussed. Moreover, we propose future research topics from the automotive manufacturing systems perspective.

Throughput analysis of production systems: recent advances and future topics

Bottlenecks within a production line significantly reduce the productivity. Quick and correct identification of the bottleneck locations can lead to an improvement in the operation management of utilising finite manufacturing resources, increasing the system throughput, and minimising the total cost of production. Most of the current bottleneck detection schemes focus on the long-term bottleneck detection problem and an analytical or simulation model is usually needed. Due to recent developments, short-term process control and quick decision making on the plant floor have emerged as important qualities for operation management. This research proposes a new data driven method for throughput bottleneck detection in both the short and long term. The method utilises the production line blockage and starvation probabilities and buffer content records to identify the production constraints without building an analytical or simulation model. The method has been verified both analytically and by simulation. An in...

Data driven bottleneck detection of manufacturing systems

This paper provides a novel method for detecting bottlenecks in manufacturing systems and the shifting of these bottlenecks. All manufacturing systems are constrained by one or more bottlenecks. Improving the bottleneck will improve the whole system. Yet, finding the bottleneck is no trivial task. Furthermore, the system may change over time or due to random events, and subsequently the bottleneck may shift from one machine to another machine. The shifting bottleneck detection method determines the bottleneck based on the duration a machine is active without interruption. The method is very robust, easy to apply and able to detect the primary and secondary bottlenecks in a wide range of production systems. This allows the use of simulation to predict bottlenecks for both steady state and variable systems. The measurement of the likelihood of a machine being the bottleneck aids in the decision-making regarding the allocation of the available resources.

Shifting bottleneck detection

The bottleneck (BN) of a production line is a machine that impedes the system's performance in the strongest manner. It has been shown in previous work that the so-called downtime bottlenecks (DT-BNs) are of main industrial importance. In this paper, a method for DT-BN identification is developed in the framework of serial production lines with unreliable (Markovian) machines and finite buffers. The identification tool derived is based on the probabilities of machine blockages and starvations. To evaluate these probabilities, a novel aggregation technique is proposed. The results obtained are applied to the design of a production line at an automotive component plant.

http://www.productionsystemsengineering.com/Meerkov_mfg_publications/Chiang_Kuo_Meerkov_BN_DT_Markovian_2000.pdf

DT-bottlenecks in serial production lines: theory and application

Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI.

/pdf/a-hierarchical-structure-of-key-performance-indicators-for-4dumxlbv6a.pdf

A Hierarchical structure of key performance indicators for operation management and continuous improvement in production systems

In this work, a new definition of production systems bottlenecks is formulated and analyzed. Specifically, a machine is defined as the bottleneck if the sensitivity of the system's performance index to this machine's production rate in isolation is the largest. Although appealing from the systems point of view, this definition suffers a deficiency due to the fact that the sensitivities involved cannot be either measured on-line or efficiently calculated off-line. To avoid this, the paper develops a method based on indirect but real-time data. From this point of view, the main result of the work is as follows: The bottleneck machine in a serial production line can be identified by analyzing relationships between the so-called manufacturing blockage and manufacturing starvation of each machine. This leads to a simple rule for bottleneck identification. The rule requires neither the calculation of the production rate sensitivities nor the production rate itself. When the probabilities of manufacturing blockages and starvations are not available from on-line measurements, the paper presents their analytical estimates which, under certain conditions, can be used for bottleneck identification. Finally, a case study at an automotive component plant is described.

/pdf/bottlenecks-in-serial-production-lines-a-system-theoretic-4qscwq1c2h.pdf

SM Meerkov

Papers

Bottlenecks in serial production lines: A system-theoretic approach