Loading and scheduling for flexible manufacturing systems with controllable processing times

This study addresses the problem of determining the allocation of operations and their tools to machines, the operation processing times and the allocation/sequence of the parts to be processed on each machine for flexible manufacturing systems with controllable processing times. Tool lives, tool copies and tool sharing are also considered. An integer programming model is developed for the objective of minimizing the sum of operation processing and tardiness costs. Then, iterative algorithms are proposed that solve the two subproblems iteratively, where the loading subproblem is solved by a modified bin packing algorithm under initial processing times and the resulting scheduling subproblem is solved by a priority scheduling method while modifying the loading plans and operation processing times iteratively. Computational experiments were carried out, and the results are reported.     

Application of genetic algorithms with dominant genes in a distributed scheduling problem in flexible manufacturing systems

Multi-factory production networks have increased in recent years. With the factories located in different geographic areas, companies can benefit from various advantages, such as closeness to their customers, and can respond faster to market changes. Products (jobs) in the network can usually be produced in more than one factory. However, each factory has its operations efficiency, capacity, and utilization level. Allocation of jobs inappropriately in a factory will produce high cost, long lead time, overloading or idling resources, etc. This makes distributed scheduling more complicated than classical production scheduling problems because it has to determine how to allocate the jobs into suitable factories, and simultaneously determine the production scheduling in each factory as well. The problem is even more complicated when alternative production routing is allowed in the factories. This paper proposed a genetic algorithm with dominant genes to deal with distributed scheduling problems, especially in a flexible manufacturing system (FMS) environment. The idea of dominant genes is to identify and record the critical genes in the chromosome and to enhance the performance of genetic search. To testify and benchmark the optimization reliability, the proposed algorithm has been compared with other approaches on several distributed scheduling problems. These comparisons demonstrate the importance of distributed scheduling and indicate the optimization reliability of the proposed algorithm.     

A proposed approach for reconfiguration of flexible assembly line systems by motion genes

This paper applies motion genes to solve the problems of reconfiguring flexible assembly line systems to cope with ever changing production requirements. The main difficulties of reconfiguring such systems are described, and an approach of using motion genes to overcome them is proposed. It is demonstrated that conveyor components can be encoded and evolved by linear and angular conveying motions. Furthermore, genetic mating can be used to generate alternative conveyor system layouts that satisfy specific production requirements and the best can be selected, based on the concept of ‘survival of the fittest’. The proposed approach is exemplified by a test case, and it is found that the reconfiguration of flexible assembly line systems by motion genes is much easier to implement than current rule based methods.     

Flexible assembly line design problem with fixed number of workstations

In the paper, we study a flexible assembly line design problem with equipment decisions. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no smaller task time. Given the cycle time and number of workstations we aim to find the assignment of tasks and equipment to the workstations so as to minimise the total equipment cost. We develop a branch and bound algorithm that uses powerful lower bounds and reduction mechanisms. Our computational experiments have revealed that our algorithm can solve large-sized problem instances in reasonable solution times.     

Reliability analysis of a flexible manufacturing cell

In this study, mathematical models are developed to study and compare the operations of a fully reliable and an unreliable flexible manufacturing cell (FMC), each with a flexible machine, a loading/unloading robot, and a pallet handling system. The operation times, loading/unloading times, and material handling times by the pallet are assumed to be random. The operation of the reliable cell is compared to that of an unreliable cell with respect to utilization of the cell components, including the machine, robot, and pallet handling system. The unreliable cell is assumed to operate under random (machine and robot) failures with constant failure rates for the machine and the robot. The pallet handling system is assumed to be completely reliable.     

A simulated annealing algorithm based on a closed loop layout for facility layout design in flexible manufacturing systems

Facility layout design problems in flexible manufacturing systems (FMS) differ from traditional facility design problems and are more difficult to solve because there are more constraints that must be considered (i.e., cell shape, cell orientation, pick-up and drop-off point positions). The focus of this paper is on the closed loop type layout, which is based on a predetermined layout pattern. This layout pattern is commonly found in manufacturing settings since it requires a simplified material handling system configuration and since it facilitates a modular and expandable layout structure. The open-field type layout problem, where there is no predetermined layout pattern, may potentially have a more efficient configuration, since there are fewer restrictions. However, this problem is more difficult to solve and may result in configurations that are not desirable due to the lack of structure or modularity. The procedure developed in this paper improves the efficiency of the closed loop configuration by changing the rectangular shape of the loop to different sizes. In many cases, the resulting closed loop layout proves to be as efficient as the open field layout. A simulated annealing procedure (SA-CL) is used to search for the configuration that minimizes the total material handling costs. A comparison of the results with existing methods indicates that, based on solution quality and computational time, the SA-CL offers a favourable alternative for efficient layout design.     

Conceptual framework for lot-sizing and scheduling of flexible flow lines

The paper considers the lot-sizing and scheduling problem for flexible flow line production facilities. Flexible flow lines are flow lines with parallel machines on some or all production stages. The objective is to find lot-sizes and a feasible schedule that minimizes set-up, inventory holding and back-order costs. Minimization of mean flow time (measured between entering the first stage and leaving the last) is a secondary objective. An integrative solution approach is presented that can incorporate the interdependencies between lot-sizing and scheduling decisions. Applications of the approach in the semiconductor industry are illustrated.     

Integrated quality and quantity modeling of a production line

During the past three decades, the success of the Toyota Production System has spurred much research in manufacturing systems engineering. Productivity and quality have been extensively studied, but there is little research in their intersection. The goal of this paper is to analyze how production system design, quality, and productivity are inter-related in small production systems. We develop a new Markov process model for machines with both quality and operational failures, and we identify important differences between types of quality failures. We also develop models for two-machine systems, with infinite buffers, buffers of size zero, and finite buffers. We calculate total production rate, effective production rate (ie, the production rate of good parts), and yield. Numerical studies using these models show that when the first machine has quality failures and the inspection occurs only at the second machine, there are cases in which the effective production rate increases as buffer sizes increase, and there are cases in which the effective production rate decreases for larger buffers. We propose extensions to larger systems. Correspondence to: Stanley B. GershwinWe are grateful for support from the Singapore-MIT Alliance, the General Motors Research and Development Center, and PSA Peugeot-Citroën.     

遗传算法用于电子枪发射系统的全局最优化设计

常用的优化设计方法 ,如单纯形法、Powell法等 ,易陷入局部最优解。而遗传算法是一种新兴的直接搜索最优化算法 ,它模拟达尔文遗传选择与自然进化的理论 ,根据“适者生存”和“优胜劣汰”的原则 ,借助“复制”、“交换”、“突变”等操作可以得到全局最优解。本文将遗传算法运用于电子枪发射系统的最优化设计 ,得到了使交叠点半径尽可能小的发射系统的最佳结构和相应电参量     

Optimal Design of Alloy Steels Using Multiobjective Genetic Algorithms

Determining the optimal heat treatment regimen and the required weight percentages for the chemical composites to obtain the desired mechanical properties of steel is a challenging problem for the steel industry. To tackle what is in essence an optimization problem, several neural network-based models, which were developed in the early stage of this research work, are used to predict the mechanical properties of steel such as the tensile strength (TS), the reduction of area (ROA), and the elongation. Because these predictive models are generally data driven, such predictions should be treated carefully. In this research work, evolutionary multiobjective (EMO) optimization algorithms are exploited not only to obtain the targeted mechanical properties but also to consider the reliability of the predictions. To facilitate the implementation of a broad range of single-objective and multi-objective algorithms, a versatile Windows 2000®-based application is developed. The obtained results from the single-objective and the multiobjective optimization algorithms are presented and compared, and it is shown that the EMO techniques can be effectively used to deal with such optimization problems.     

Evaluation of performance measures for representing operational objectives of a mixed model assembly line balancing problem

Performance evaluation of a mixed model assembly line is complicated in nature. For some configurations of the mixed model line, operational objectives can directly be evaluated; however, in others some performance measure is required for evaluating the operational objective. This paper reports a comprehensive comparative study of performance measures as to their relevance in representing the operational objectives of a mixed model assembly line balancing problem of type II. Two performance measures are proposed in this work. A genetic algorithm has been developed for comparing the proposed measures with eight others in an effort to investigate their ability to equalize workload along with minimizing cycle time. Through statistical analysis, one of the proposed performance measures has been established to perform better than the others. Application of the performance measures to balance an assembly line taken as part of an industrial case study also corroborates the results obtained by statistical analysis.     

Analysis of refrigerant flow and deformation for a flexible short-tube using a finite element model

A finite element model was used to simulate single-phase flow of R-22 through flexible short-tubes. The numerical model included the fluid-structure interaction between the refrigerant and the deformation of the short-tube as upstream pressure was varied. The finite element model was developed using a commercially available finite element package. Short-tubes with moduli of elasticity ranging from 5513 to 9889 kPa were studied. Four upstream and downstream pressures were applied and the upstream subcooling was held at a constant value of 16.7 °C. Mass flow rates from the numerical model were compared to available published experimental results. The study showed that upon deformation the short-tube resembled the shape of a converging-diverging nozzle. Both tube inlet and outlet had a chamfered-like shape after deformation which reduced the pressure drop at the tube inlet. The smaller the modulus of the tube, the larger the chamfered-like angle at the inlet and the higher the pressure drop along the tube due to the higher tube contraction. The results illustrated that as the upstream pressure was increased by 45%, there was almost a 60% decrease in the flow area. The more flexible (5513 kPa) short-tube restricted the mass flow rate more than the most rigid (9889 kPa) short-tube used in this study. The mass flow rates estimated with the finite element model were as much as 14% higher than those from experimental results reported in the literature.     

被减振物体连接于弹性地基时动力吸振器的设计

当被减振物体连接于弹性地基时,定义被减振物体与弹性地基连接点处的动刚度,给出被减振物体幅频响应和振幅放大系数的计算公式。利用有限元方法计算不同弹性特性的地基与被减振物体连接点处的动刚度。分析被减振物体与弹性地基连接点处的动刚度对被减振物体振动的影响。计算结果表明：当连接点处的动刚度大于５０倍的被减振物体与弹性地基的连接刚度时,可基本忽略弹性地基对吸振器设计的影响。该计算方法和相关结论可为被减振物体连接于弹性地基上时,动力吸振器的设计提供借鉴。     

遗传算法用于衍射光学元件的优化设计

提出了一种基于遗传算法的衍射光学元件优化设计方法;在衍射光学元件设计中遗传算法运行参数对遗传算法性能有一定的影响:采用较大的群体规模,遗传算法越容易获得最优解;交叉算子越大,遗传算法全局搜索能力越强;选择算子对遗传算法的影响不是太大;如果要进一步提高解的精度,可选取较大的终止代数。数值计算结果表明,用遗传算法优化设计的衍射光学元件,其误差小于 5.2%,衍射效率达到 91.2%。遗传算法很适合衍射光学元件的优化设计。     

Design of a bi-directional illumination system for a dual view capsule endoscope

The capsule endoscope is an important tool for the intestinal examination. But the main disadvantage of the traditional capsule endoscope is the limited field of view. In order to solve this problem, the dual view capsule endoscope (DVCE) was developed. In this work, a dual view illumination system is designed for a DVCE. The dual view illumination system is divided into two sub-systems with a front view illumination lens and a back view illumination lens. The Bézier curves for the front view and back view illumination lenses are used for optimization, based on which we change the radiation pattern of the LED so that the dual view illumination design can support energy for the front view and back view simultaneously while achieving low power consumption and high efficiency. Moreover, a non-uniform illumination process is used to compensate for the problem of uniformity and relative illumination for the DVCE lens. Through this design, we can obtain a uniformity of 91% and an efficiency of 25.2% for front view illumination and uniformity of 91% and an efficiency of 23.5% for back view illumination. Finally, tolerance analysis can also be completed for mass production.     

Genetic algorithm optimization of a firewater deluge system

Safety systems are designed to operate when certain conditions occur and to act to prevent their development into a hazardous situation. Failure of a safety system for a potentially hazardous industrial system or process may have catastrophic consequences, possibly injuring members of the work force or public and occasionally resulting in loss of life. The purpose of this paper is to describe a design optimization scheme using genetic algorithms applied to a firewater deluge system, which uses available resources to the best possible advantage to obtain an optimal safety system design. Copyright © 2003 John Wiley & Sons, Ltd.     

Evolutionary experiments for self-assembling amphiphilic systems

Some amphiphilic molecules in particular environments may self-assemble and originate chemical entities, such as vesicles, which are relevant in technological applications. Experimentation in this field is difficult because of the high dimensionality of the search space and the high cost of each experiment. To tackle the problem of designing a relatively small number of experiments to achieve the relevant information on the problem, we propose an evolutionary design of experiments based on a genetic algorithm. We built a particular algorithm where design and laboratory experimentation interact leading the search toward the optimality region of the space. To get insight in the process we then modelled the experimental results with different classes of regression models; from modelling we could identify the special role played by some molecules and the relevance of their relative weight in the composition. With modelling we “virtually” explored the experimental space and predicted compositions likely to generate very high yields. Models then provide valuable information for the redesign of the experiments and can be considered as an essential addition to the evolutionary approach.     

Feature-based design for process planning of machining processes with optimization using genetic algorithms

The development of a feature-based design environment that can be applied in the concept-to-manufacturing stages of the machining process is explained. It is broadly divided into four modules, namely, feature-based design (FBD) environment, virtual factory environment (VFE), operation-based feature mapping (OBFM) and optimization using genetic algorithms (GA). The feature-based design environment module is used for the design, modelling, synthesis, representation and validation of the components for machining application. It uses integrated features, which are predefined as feature templates in the feature library. While instancing these integrated features, they get/derive the information required for the design, modelling, process planning and manufacturing stages of the components as their attributes, from the user/knowledge base. After creating the component, integrated features present in it are validated with respect to its application, namely machining process. The VFE module defines the mathematical model of the factory in the computer, which provides the database for operations, machines, cutting tools, work pieces, etc. The knowledge base maps validated features of the component into operation sets in the first phase of the OBFM stage. Each operation in the operation sets can be carried out using different machines and cutting tools in the factory. All these possible choices are obtained in the second phase of OBFM. GA is used to find the optimal sequence of operations, machines and cutting tools for different criteria. Provisions are also available to generate NC codes for operations, which are to be carried out with NC or CNC machines, if selected. Thus, the optimal process plan for the selected criteria with respect to the given factory environment is found for the modelled component. The feature-based design system developed is built on existing CAD, programming and spread-sheet software tools, namely CATIA®, MS-Visual Basic® and MS-Excel®, which not only save developmental effort, but also make full use of the functionalities of these commercial softwares. This paper explains the developed system with a case study.     

Evaluating order of circuits for deadlock avoidance in a flexible manufacturing system

In modern highly automated flexible manufacturing systems, various parts are processed concurrently. Due to the concurrency and shared equipment usage, deadlock is a common problem that causes loss of productivity. When such a system is modelled by a digraph, existence of circuits in such a graph is a necessary condition for deadlock and knots and the order of circuits are closely related to impending deadlocks – a type of deadlock that is more difficult to detect. A deadlock avoidance algorithm that dynamically evaluates the order of circuits is presented. The algorithm is highly permissive since the order evaluation captures more part flow dynamics, especially when there exist multiple knots in the digraph model. It also runs in polynomial time once the set of circuits of the digraph is given. Simulation results are provided to illustrate the application of the algorithm.     

A novel magnetron sputtering for flexible coatings as a function for production of high quality films

A novel sputtering technique combining the symmetric compressive magnets with cylindrical cathode has been developed to mass produce high-quality oxide and nitride films on plastic sheets. The discharge characteristics of our sputtering can supply about three times larger power efficiencies than that of the conventional magnetron sputtering. Moreover, in continuous dielectric sputtering experiments, the substrate temperature was kept lower than 60 °C. The refractive index of SiN_X and SiO₂ thin film at 500 nm is 1.86 and 1.46 respectively. Moreover, 4 layered anti-reflection coatings of silicon nitride and oxide films deposited on both sides of the PET sheet is achieved to fabricate, and the reflection less than 1% is realized in the range from 420 to 680 nm.