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

Simulation study for investment decisions on the EcoBoost camshaft machining line

Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company’s Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area. Keywords: simulation modelling, closed-loop network, automotive production system

Manufacturing flow line systems: a review of models and analytical results

The most important models and results of the manufacturing flow line literature are described. These include the major classes of models (asynchronous, synchronous, and continuous); the major features (blocking, processing times, failures and repairs); the major properties (conservation of flow, flow rate-idle time, reversibility, and others); and the relationships among different models. Exact and approximate methods for obtaining quantitative measures of performance are also reviewed. The exact methods are appropriate for small systems. The approximate methods, which are the only means available for large systems, are generally based on decomposition, and make use of the exact methods for small systems. Extensions are briefly discussed. Directions for future research are suggested.National Science Foundation (U.S.) (Grant DDM-8914277

Real-Time Analysis and Control of Serial Production Lines for Energy Efficient Manufacturing

Productivity analysis, operation control and energy consumption reduction have been the central topics in manufacturing research and practice. They are closely related to each other. Control of production operations is considered as one of the most economical methods to improve energy efficiency in manufacturing systems, while system performance analysis serves as the base of production control. On the other hand, effective operation control can result to energy efficiency in manufacturing. Steady state analysis has been investigated extensively; however, transient analysis remained largely unexplored. Our research focuses on system modeling, performance analysis, and real-time operation control of serial production lines with unreliable machines and finite buffers, especially in transient period, with Bernoulli or geometric reliability. Analytical results, practical case studies and applications for energy efficient manufacturing are provided. A simulation using ARENA software to reproduce and analyze brewery production line is performed

Green and lean control of cyclic pallet systems

Reduction of energy consumed by a manufacturing system to turn raw parts to finished products is a big step towards the green and lean production. In this study the energy efficiency of a one-loop pallet system, a main tool to handle and locate various part types in a cyclic production line, is investigated. The main goal is to obtain the minimal energy consumption in the pallet system drive unit through an optimally controlled and coordinated motion of pallets. To achieve the mentioned goal, first the mean value of the pallet system energy consumption is mathematically modeled. Later, this energy model is utilized as an objective function within an optimization model including constraints on system crucial properties such as cyclic and dynamic behavior, queueing policy, and buffer size. The solution of the optimization problem gives the optimal values of the system control variables, namely, number of pallets and conveyor velocity. To demonstrate the application of this optimization model in practice, three case studies are introduced. The results of these studies show that a significant amount of the energy consumption may be saved by applying the suggested green control

Efficient buffer design algorithms for production line profit maximization

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 447-465).A production line is a manufacturing system where machines are connected in series and separated by buffers. The inclusion of buffers increases the average production rate of the line by limiting the propagation of disruptions, but at the cost of additional capital investment, floor space of the line, and inventory. Production lines are also a special case of assembly/disassembly systems as well as closed-loop systems. This thesis makes contributions to production system profit maximization. The profit of a production line is the revenue associated with the production rate minus the buffer space cost and average inventory holding cost. We assume that machines have already been chosen and therefore our only decision variables are the buffer sizes and the loop population. The difficulties of the research come from evaluation and optimization. We improve evaluation of loop systems. The optimization problem is hard since both the objective function and the constraints are nonlinear. Our optimization problem, where we consider the nonlinear production rate constraint and average inventory cost, is new. We present an accurate, fast, and reliable algorithm for maximizing profits through buffer space optimization for production lines, and extend the algorithm to closed-loop systems and production lines with an additional maximum part waiting time constraint. A nonlinear programming approach is adopted to solve the optimization problem. Two necessary modifications are proposed to improve the accuracy of the existing loop evaluation method before optimization of loops is studied. An analytical formulation of the part waiting time distribution is developed for two-machine one-buffer lines. It is used in the profit maximization for production lines with both the production rate constraint and the maximum part waiting time constraint. Numerical experiments are provided to show the accuracy and efficiency of the proposed algorithms. Finally, a segmentation method and an additive property of production line optimization are studied. They enable us to optimize very long lines rapidly and accurately.by Chuan Shi.Ph.D

An Analytical Approach to Cycle Time Evaluation in an Unreliable Multi-Product Production Line with Finite Buffers

This thesis develops an analytical approximation method to measure the performance of a multi-product unreliable production line with finite buffers between workstations. The performance measure used in this thesis is Total Cycle Time. The proposed approximation method generalizes the processing times to relax the variation of product types in a multi-product system. A decomposition method is then employed to approximate the production rate of a multi-product production line. The decomposition method considers generally distributed processing times as well as random failure and repair. A GI/G/1/N queuing model is also applied to obtain parameters such as blocking and starving probabilities that are needed for the approximation procedure. Several numerical experiments under different scenarios are performed, and results are validated by simulation models in order to assess the accuracy and strength of the approximation method. Consequent analysis and discussion of the results is also presented

Sustainable and robust Control of Cyclic Pallet Systems

A proper control of a system to get a desired function and increase the system lifetime is a crucial step towards the sustainable paradigm. In this paper, such a control is designed for a cyclic pallet system to achieve a minimal force on its drive unit, meet safety conditions on the system chain tension force and the momentum of pallets, and fulfill the desired production rate. The optimal values of the control parameters, namely number of pallets and conveyor velocity, are obtained through solving a linear optimization model. The objective function in the model defines the average force on the drive unit in a cycle production. In addition, the related constraints characterize the pallet system properties such as cyclic and dynamic behavior, buffer size, constant work in process, and safety specifications. The robustness of the optimal control is analyzed, using a worst but safe control strategy. The optimal control and the robustness analysis are applied to some case studies, and the results are evaluated and discussed