Ningjian Huang

Throughput analysis of production systems: recent advances and future topics

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.

Designing production systems for quality: Research opportunities from an automotive industry perspective

We explore the intersection of two research areas: quality and production system design. Conventional wisdom holds that a products quality is affected much more by its design than its production. Nevertheless, we argue that the production system used to manufacture a product does indeed affect its quality. We briefly review the limited literature on the intersection of quality and production system design and suggest several new research issues that are important to industry.

Survey of recent advances on the interface between production system design and quality

Product designs impact on quality is widely recognized. Less well recognized is the impact of production system design on quality. As quality can be improved by integrating it with the design of the product, so it can be improved by integrating quality with the design of the production system. This article provides evidence of the production systems influence on quality and surveys recent advances on the interface between quality and production system design including the design of the production systems quality control process. After mapping the literature, we identify opportunities for future research.

Quality Evaluation in Flexible Manufacturing Systems: A Markovian Approach

The flexible manufacturing system (FMS) has attracted substantial amount of research effort during the last twenty years. Most of the studies address the issues of flexibility, productivity, cost, and so forth. The impact of flexible lines on product quality is less studied. This paper intends to address this issue by applying a Markov model to evaluate quality performance of a flexible manufacturing system. Closed expressions to calculate good part probability are derived and discussions to maintain high product quality are carried out. An example of flexible fixture in machining system is provided to illustrate the applicability of the method. The results of this study suggest a possible approach to investigate the impact of flexibility on product quality and, finally, with extensions and enrichment of the model, may lead to provide production engineers and managers a better understanding of the quality implications and to summarize some general guidelines of operation management in flexible manufacturing systems.

Production system design to achieve energy savings in an automotive paint shop

Vehicle painting typically consumes the largest amount of energy in an automotive assembly plant. Effective reduction of energy usage in paint shops will lead to significant savings. Substantial effort has been devoted to reducing energy usage in paint shops through renovating the painting process and equipment. In this paper, we introduce a case study at an automotive paint shop to show that the energy consumption can be reduced significantly through production system design. Specifically, by selecting the appropriate repair capacity, the number of repainted jobs can be reduced, and less material and energy will be consumed. In addition, less atmospheric emissions would be generated during the painting process. Such a technique does not need to invent new chemicals, new painting processes or new control systems in painting booths and ovens. It provides an alternative way for energy and emission reduction to achieve energy-efficient and environmentally friendly manufacturing.

Simulation study of a bottleneck-based dispatching policy for a maintenance workforce

Maintenance is important for production operations and for continuous improvement. Appropriate dispatching of the maintenance workforce to quickly respond to equipment failures and carry out preventive services can improve system productivity. The first-come-first-served policy is typically used in many manufacturing industries. In this paper, we present a priority-based dispatching policy, a dynamic bottleneck policy, based on the analysis of real-time data. In such a policy, priority is assigned to the bottleneck machine after a fixed time period, and the maintenance worker will service the high-priority machine (i.e. bottleneck machine) first when multiple service requests are received. It is shown by extensive simulation experiments that this policy can lead to a greater improvement in system throughput compared with the first-come-first-served policy. To implement such a policy, the appropriate time period for data collection and the frequency for carrying out bottleneck analysis are investigated. In addition, a sensitivity study suggests that the results obtained are insensitive to machine downtime, efficiency, and reliability models.

A Simulation-Based Tool for Energy Efficient Building Design for a Class of Manufacturing Plants

This paper explores energy efficient building design for manufacturing plants. Many efforts have been directed into the field of building design optimization concerning building energy performance, but most of the studies focus on residential buildings or public buildings. Very limited research results studying plants buildings have been reported. However, plants buildings have certain unique features that make the design problem more challenging. Furthermore, the approaches presented in the current publications could not guarantee the performance of their designs if the computation capacity is limited. This paper attempts to address these two issues. First, an EnergyPlus-integrated overall energy consumption estimation framework is developed for a class of manufacturing plants, where the environmental conditions would not affect the energy consumption of the production processes. Based on that, the building design problem for this type of manufacturing plants is formulated as a stochastic programming problem concerning uncertainties arising from the future weather conditions and energy prices, where seasonal production scheduling optimizing is incorporated when estimating the performance of building designs. Second, Ordinal Optimization (OO) method is introduced to solve the problem so as to quantitatively guarantee a high probability of finding satisfactory designs while reducing the computation burden. A numerical example is provided, showing our solution method performs effectively in finding a satisfactory design.

Modeling and analysis of a multiple product manufacturing system with split and merge

This paper presents an iterative approach to model and analyze one type of flexible manufacturing systems with common lines and dedicated branches to process different products. The mathematical procedures, associated with the justification of convergence and accuracy, are provided. A case study is presented to illustrate the applicability of the method.

A Quality Flow Model in Battery Manufacturing Systems for Electric Vehicles

Improving quality in large volume battery manufacturing systems for hybrid and electric vehicles is of significant importance. In this paper, we present a flow model to analyze and improve product quality in electrical vehicle battery assembly lines with 100% inspections and repairs for defective parts. Specifically, a battery assembly line consisting of multiple inspection stations is considered. After each inspection, defective parts will be repaired and sent back to the line. A quality flow model is introduced to analyze quality propagations along the battery production line. Analytical expressions of final product quality are derived and structural properties, such as monotonicity and sensitivities, are investigated. A bottleneck identification and mitigation method is introduced to improve quality performance. Finally, a case study is presented to illustrate the applicability of the method.

Optimal vehicle batching and sequencing to reduce energy consumption and atmospheric emissions in automotive paint shops

Reducing energy consumption and carbon emissions is an important issue to achieve sustainable manufacturing. In automotive assembly plants, the largest amount of energy consumption and atmospheric emissions is in paint shop. Optimising the energy usage to pursue maximum energy savings, and reducing carbon dioxide equivalent emissions are of significant importance in automotive paint shops. Instead of inventing new chemicals, new painting processes or new control systems in painting booths and ovens, our research focuses on developing an optimal batch and scheduling procedure of vehicles to achieve the goal of energy and emission reduction. Specifically, by selecting appropriate batch and sequence policies, the paint quality can be improved and repaints can be reduced so that fewer material and energy will be consumed, and less atmospheric emissions will be generated. It is shown that such scheduling and control method can lead to significant energy savings and emission reduction with no extra investment, nor changes to existing painting processes.