Factory Models for Manufacturing Systems Engineering

We review MIT research in manufacturing systems engineering, and we describe current and possible future research activities in this area. This includes advances in decomposition techniques, optimization, token-based control systems analysis, multiple part types, inspection location, data collection and several other topics.Singapore-MIT Alliance (SMA

Performance Evaluation of Remanufacturing Systems

Implementation of new environmental legislation and public awareness has increased the responsibility on manufacturers. These responsibilities have forced manufacturers to begin remanufacturing and recycling of their goods after they are disposed or returned by customers. Ever since the introduction of remanufacturing, it has been applied in many industries and sectors. The remanufacturing process involves many uncertainties like time, quantity, and quality of returned products. Returned products are time sensitive products and their value drops with time. Thus, the returned products need to be remanufactured quickly to generate the maximum revenue. Every year millions of electronic products return to the manufacturer. However, only 10% to 20% of the returned products pass through the remanufacturing process, and the remaining products are disposed in the landfills. Uncertainties like failure rate of the servers, buffer capacity and inappropriate preventive maintenance policy would be highly responsible the delays in remanufacturing. In this thesis, a simulation based experimental methodology is used to determine the optimal preventive maintenance frequency and buffer allocation in a remanufacturing line, which will help to reduce the cycle time and increase the profit of the firm. Moreover, an estimated relationship between preventive maintenance frequency and MTBF (Mean Time Between Failure) is presented to determine the best preventive maintenance frequency for any industry. The solution approach is applied to a computer remanufacturing and a cell phone remanufacturing industry. Analysis of variance and regression analysis are performed to denote the influential factors in the remanufacturing line, and optimization is done by using the regression techniques and ANOVA results

Analytical evaluation of the output variability in production systems with general Markovian structure

Performance evaluation models are used by companies to design, adapt, manage and control their production systems. In the literature, most of the effort has been dedicated to the development of efficient methodologies to estimate the first moment performance measures of production systems, such as the expected production rate, the buffer levels and the mean completion time. However, there is industrial evidence that the variability of the production output may drastically impact on the capability of managing the system operations, causing the observed system performance to be highly different from what expected. This paper presents a general methodology to analyze the variability of the output of unreliable single machines and small-scale multi-stage production systems modeled as General Markovian structure. The generality of the approach allows modeling and studying performance measures such as the variance of the cumulated output and the variance of the inter-departure time under many system configurations within a unique framework. The proposed method is based on the characterization of the autocorrelation structure of the system output. The impact of different system parameters on the output variability is investigated and characterized. Moreover, managerial actions that allow reducing the output variability are identified. The computational complexity of the method is studied on an extensive set of computer experiments. Finally, the limits of this approach while studying long multi-stage production lines are highlighted. © 2013 Springer-Verlag Berlin Heidelberg

Throughput enhancement with parallel redundancy in multi-product flow line system

We develop a new analytic approximation method to replace a set of parallel machines by an equivalent machine in a series-parallel flow line with finite buffer. We develop our method based on discrete state Markov chain. The proposed technique replaces a set of parallel machines at a work centre by an equivalent machine in order to obtain a traditional flow line with machines in series separated by intermediate buffers. We derive equations for the parameters of the equivalent machine when it operates in isolation as well as in flow line. The existing analytic methods for series-parallel systems can tract only lines with a maximum of two machines in series and a buffer in-between them. The method we propose in this thesis can be used in conjunction with an approximation method or simulation to solve flow lines of any length. We also model and evaluate the performance of series-parallel systems manufacturing more than one product types with predefined sequence and lot size. We address this issue for a considerable longer flow line system with finite buffer which is common in industry. We consider the set-up time of the machines as the product type changes, deterministic processing times and operation dependent failures of the machines. We analyze the effects of buffer and number of machines in parallel on the performance of series-parallel systems

Adaptive policy of buffer allocation and preventive maintenance actions in unreliable production lines

Abstract The buffer allocation problem is an NP-hard combinatorial optimization problem, and it is an important design problem in manufacturing systems. The research proposed in this paper concerns a product line consisting of n unreliable machines with n − 1 buffers and a preventive maintenance policy. The focus of the research is to obtain a better trade-off between the buffer level and the preventive maintenance actions. This paper proposes a dynamic control of the buffers' level and the interval between two consecutive preventive actions. The set of the parameter of the proposed policy allows choosing the reduction in the costs or the increment of the throughput rate. A simulation model is developed to test the proposed model to the solution proposed in the literature. The proposed policy leads to better results in terms of total costs reduction keeping high production rate, while the design of a fixed level of buffer works better for lower production rates required

Approximate performance analysis of production lines with continuous material flows and finite buffers

In this paper, we analyze production lines consisting of a number of machines or servers in series with a finite buffer between each pair of machines. The flow of products through the machines is continuous. Each machine suffers from breakdowns, because of, for example, failures, cleaning and changeover. The up- and downtimes are independent and generally distributed. We develop a new method to efficiently and accurately estimate the throughput and the mean buffer content of the production line. This method relies on decomposition of the production line into two-stage, one-buffer subsystems aggregating the up- and downstream part of the line. For each subsystem, the parameters of the aggregate up- and downtimes are determined iteratively by employing matrix-analytic techniques. The proposed method performs very well on a large test set consisting of over 49,000 cases. Remarkably, the performance of the method does not deteriorate in case of highly unpredictable up- and downtimes, as often seen in practice. We apply the method to a bottling line at brewery Heineken Den Bosch and an assembly line at NXP Semiconductors

Modeling and Optimization of Disassembly Systems with a High Variety of End of Life States.

Remanufacturing is a promising product recovery method that brings new life to cores that otherwise would be discarded thus losing all value. Disassembly is a sub-process of remanufacturing where components and modules are removed from the core, sorted and graded, and directly reused, refurbished, recycled, or disposed of. Disassembly is the backbone of the remanufacturing process because this is where the reuse value of components and modules is realized. Disassembly is a process that is also very difficult in most instances because it is a mostly manual process creating stochastic removal times of components. There is a high variety of EOL states a core can be in when disassembled and an economic downside due to not all components having reuse potential. This thesis focuses on addressing these difficulties of disassembly in the areas of sequence generation, line balancing, and throughput modeling. In Chapter 2, we develop a series of sequence generation models that considers the material properties, partial disassembly, and sequence dependent task times to determine the optimal order of disassembly in the presence of a high variety of EOL states. In Chapter 3, we develop a joint precedence graph method for disassembly that models all possible EOL states a core can be in that can be used with a wide variety of line balancing algorithms. We also develop a stochastic joint precedence graph method in the situation where some removal times of components are normal random variables. In Chapter 4, we further advance the analytical modeling framework to analyze transfer lines that perform routing logics that result from a high variety of EOL states, such as a restrictive split routing logic and the possibility that disassembly and split operations can be performed at the same workstation.PhDIndustrial and Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111570/1/robriggs_1.pd

An Aggregation Procedure for Simulating Manufacturing Flow Line Models

We develop a formal method for specifying an aggregate discrete-event simulation model of a production flow line manufacturing system. The methodology operates by aggregating production stations or resources of a flow line. Determining the specifications for representing the aggregated resources in a simulation model is the focus of our presentation. We test the methodology for a set of flow lines with exponentially distributed arrival and service times. Comparisons between analytical and simulation results indicate the aggregation approach is quite accurate for estimating average part cycle time