An inter-machine material handling system for micro-manufacturing based on using a standard carrier

This paper presents a framework of intelligent manufacturing scheduling and control with specific applications to operations of rail-guided vehicle systems (RGVS). A RGVS control architecture is discussed with a focus on a simulated experiment in operations of the load/unload area of a real industrial flexible manufacturing system (FMS). In the operation stage of a material handling system (MHS), all shop floor data are subject to change as time goes. These data can be collected using a data acquisition device and stored in a dynamic database. The RGVS simulator used in this experimental study is designed to incorporate some possible situations representing existing material handling scenarios in order to evaluate alternative control policies. At the development stage of the controller, all possible combinations of most commonly encountered scenarios such as RGV failures, production schedule changes, machine breakdowns, and rush orders are to be simulated and corresponding results collected. The data are then structured into training data pairs to properly train an artificial neural network. The neural network, trained by using input/output data sets obtained from a number of simulation runs, will then provide control strategy recommendations. At the application stage, whenever an abnormal scenario occurs, a pre-processor will be activated to pre-screen and prepare an input vector for the trained neural network. If such an abnormal scenario falls outside the existing domain of data sets employed to train the neural network, as judged by the MHS supervisory controller, an off-line training module will be activated to eventually update the neural network. The recommended control strategies will be transmitted to the MHS control for real-time execution. If there is no further abnormal event detected, the dynamic data base (DDB) module simply continues to monitor the MHS activities. The proposed MHS control system combines the features of example based neural network technology and simulation modeling for true intelligent, on-line, pseudo real-time control. Not only will the system assure that feasible material handling control actions be taken, but also it will implement better control decisions through continuous learning from experiences captured as the operation time of the MHS accumulates.

In today’s competitive global market, industries and manufacturing companies demand adjustable sizes, higher quality, flexibility, and shorter lead time types of products to be manufactured. Companies need to attain customer satisfaction and cost reduction in production operations. A material Handling System is a way to accomplish this goal since they directly impact production. This study aims to design an in-house Material Handling system that could be efficient for the production it serves. The material handling system design was made to pick and place the head expander on the vibrating machine from the floor beside the machine. The vibration testing components are placed on the head expander where it is placed on the vibration machine to check the frequencies the component can absorb. This componentis used in aerospace industries. The material used for building the Material Handling System is mild steel. By analyzing the possibilities from literature review and empirical study first problems and challenges related to material handling system are identified, then possible features that the system should possess are observed and design is built according to the selected features. The design of this Material Handling System is made by using Solid works software. The developed model is further analyzed by the boundary condition for total deformation when the constant load acts on the model at different places. Dynamic analysis to be made for the vibration absorbed by the material handling system. Here both static and dynamic analysis is made forthe structural model using ANSYS WORKBENCH software.

As semiconductor device ground rules become more stringent, lithographers are driven to reduce the magnitude of system error budget components to near atomic scale levels. Near term requirements (1995) for semiconductor photomask image placement have already been defined at 25 nm and are presumed to become tighter. Error contributions from both the stage metrology platform and material handling subsystems must be improved to 10 nm, thus allowing the balance of the error budget to be apportioned to the electron-optics and the electronic subsystems. As a result, a new, automated state-of-the-art Material Handling System (MHS) was designed for the Lepton EBES4 E-Beam Reticle Generator. This MHS is capable of handling multiple products such as reticles up to 9 in. (229 mm), x-ray masks, and wafers. Accuracy, required to support future E-beam pattern-writing applications for the production of 256 Mb and 1 Gb DRAM substrates, was the principle objective in its design. Therefore key attributes of the MHS are: (1) Precise substrate positioning with a resolution of (lambda) /120 achieved by means of two high-stability dual linear/angular interferometers combined in a single, compact optical assembly. (2) Stringent thermal management within the vacuum environment via a unique low-pressure (50 torr) gas conduction isotherm mode of action, which represents a new approach for rapid substrate temperature equilibrium to less than +/- 0.02 degree(s)C control. This paper focuses on how the MHS design addresses the minimization of mechanical error contributions to lithographic accuracy. Tests results of numerous critical parameters are presented (aligner/robot-corrected substrate positioning accuracy, temperature equilibration and stability, stage smoothness of motion, and electromagnetic interference). In addition, 3D finite element models are included to demonstrate induced static and random distortions, and dynamic modes of the metrology platform.

Mass management and production of customized products requires material handling systems (MHS) which are flexible and responsive enough to accommodate dynamic and real-time changes in material handling tasks. Towards this goal, we develop a novel control framework to improve the flexibility and responsiveness of material handling systems. Flexibility is achieved by using multi-commodity flow network optimization to find the most optimized job sequence in terms of minimum transfer steps. Responsiveness is achieved by the use of a matrix-based discrete event (DE) supervisory controller to dispatch equipment control commands in real-time based on real-time sensor information, according to the optimized sequence. By modeling the MHS network as multi-commodity flow network to define job routes, and using the matrix-based DE controller to implement the job routes in real-time, the users achieve a seamlessly integrated solution to control the execution of transfer jobs that covers the supervisory planning stage through the real-time actual dispatching decisions. The proposed control framework is evaluated on an industrial case study of airfreight terminal material handling and simulation results show its effectiveness.

Material handling systems (MHS) include a wide range of systems and equipment that are used for handling, movement, storage and control of materials during manufacturing. MHS can represent a significant portion of the cost to make a product and there can be significant cost savings in manufacturing processes if unexpected failures of such systems can be avoided and maintenance costs lowered. This paper first surveys the common maintenance practices of MHS including three typical warehouse MHS e.g. automatic picking system (APS), goods to destination (GDS), and Erector. The survey from end users shows that the majority of the companies does not keep the record of their past failures or improve their maintenance practices after major failures occur. Even the end users with more advanced maintenance programs use more reactive maintenance approaches, as opposed to preventive maintenance approaches which have the potential to lower the chances of unexpected failures and costly repairs. The present paper also r...

A material handling and logistic system using an automated crane

An integrated manufacturing system with a finite capacity consisting of a set of work stations, a loading station and unloading stations linked by a material handling system is considered. Each work station has a local storage, a set of flexible machines capable of processing workpieces belonging to the same family of parts and an unloading station. Each workpiece requires only one stage of operation which may receive it from either one of the work stations. The integrated material handling system consists of a set of line conveyors, each with a specified length, velocity and capacity. In this paper, an open queueing network model is developed to analyse the effects of the loading, the material handling, the storage and the processing operations on the asymptotic performance of the system. Furthermore, a methodology for controlling the congestion along the material handling system is suggested. Numerical results are also provided and the approximations results are compared against those from a si...

A well-planned arrangement of manufacturing departments on a two-dimensional planar region considerably increases the efficiency of its production systems, which is termed facility layout problem (FLP). Conventional layout design approach often designs intercell layout (determining exact location of each department on shop floor area) and flow path layout design of material handling system (MHS) step by step in a sequential manner. This results in suboptimal solutions for FLP. In this paper, an integrated approach is adopted to design the intercell layout and the flow path layout of MHS simultaneously. The quality of the final layout is evaluated by minimizing total material handling cost. Sequence pair (SP) representation is used for layout encoding. The translation from SP to layout is efficiently made by longest common subsequence (LCS) methodology. An elitist strategy genetic algorithm using simulated annealing (E-GASAA) as a local search mechanism is developed and tested with four test problem instances available in the literature. Elitist strategy is incorporated to enhance convergence characteristic of the proposed algorithm. It is found that the proposed E-GASAA is able to produce best solutions consistently for the test problem instance of different sizes within acceptable computational effort. In addition to that, we tried to reduce the computational load with the help of adopted LCS computation methodology and achieved a good improvement.

While designing the layout of any manufacturing organizations, the primary objective is to decide an optimal arrangement of their departments (machines or cells) in a two-dimensional shop floor (facility) satisfying desired objectives, which is termed facility layout problem (FLP). In traditional layout design philosophy, the inter-cell layout and flow path layout design of material handling system (MHS) was carried out step by step in a sequential manner. This results in sub-optimal solutions for FLP. In this paper, an integrated approach is adopted to design the inter-cell layout and the flow path layout of MHS simultaneously. The quality of the final layout is evaluated by minimizing the weighted sum of two distance-based cost objectives namely, (1) total material handling cost. (2) Distance-weighted cost of total closeness rating score. Sequence-pair (SP) representation is used for layout encoding. The translation from SP to layout is efficiently done by longest common subsequence methodology. Due to NP-hard nature of the proposed problem, an elitist strategy genetic algorithm (ESGA) is developed and tested with three test problem instances available in the literature. It is found that the proposed ESGA algorithm is able to produce the best solutions consistently, twice faster than the standard GA for the test problem instances.

Traditionally the design of Inter-cell layout and Material Handling System (MHS) of the manufacturing system is being carried out in step by step. This leads to sub-optimal solutions for facility layout problems (FLP). In this work an attempt is made to concurrently design Inter-cell layout and the MHS using a Genetic Algorithm (GA) based methodology using simulated annealing algorithm (SAA) as local search tool for a Cellular Manufacturing System (CMS) environment under open field configuration. The proposed algorithm is employed to simultaneously optimize two contradicting objectives viz. 1. Total material handling cost 2. Distance weighted cost of closeness rating score. The algorithm is tested on two different bench mark layouts and with different initial problem data sets. It is found that the proposed algorithm is able to produce approximate pareto-optimal solutions.KeywordsIntegrated Layout DesignGenetic AlgorithmMutiobjective optimization

A genetic approach to the pickup/delivery station location problem in segmented flow based material handling systems

This research examines the problem of determining the optimal fleet size for fixed-path material handling systems on the bases of performance and reliability, simultaneously. In this paper, a regression model is developed to study the relationships among various material handling system design characteristics (fleet size, guide path layout, and number of P/D stations, vehicle speed and failure rates, guide path intersection failure rates, and P/D station failure rates) and performability, measured as the average number of material moves between failures (MBF). The regression model highlights the important relationships between the selected factors and performability, and may be used to determine the performability-based optima for the controllable design characteristics.

In most physical queueing applications, customers join a queue and move forward after each service, leaving room for others to join behind them. Some queues found in material handling and transportation systems do not operate like this because the queued entities (pallets or unoccupied cars, for example) are incapable of moving forward autonomously. We develop a model for the resulting staging queue, and give simulation results for several configurations.

Recent advances in computing have allowed simulation to be used as a source of data in the real-time control of logistics systems such as Material Handling Systems (MHS). For a real-world MHS, in development by Lödige Industries GmbH, Germany, we demonstrate the benefit of generating data offline using a parametrized simulation model that real-time operational control is based on. The data consist of mappings of control situations to optimal actions respectively. Our approach allows for self-adaptation of the simulation by observing current system parameters that are fed into the model. The control automatically triggers regeneration when necessary, detects changes in the system and also proactively anticipates them, resulting in consistently high performance. We furthermore use a simulation-based look-ahead method to consider uncertainties when evaluating alternative actions. Evaluation results show a significant increase in system performance compared to fixed application of a control action and demonstrate the benefits of the self-adaptive properties.

Economic modeling is an important component of material handling system (MHS) design and analysis. Economic modeling must include an assessment of the costs and benefits of the MHS, including not only tactical costs and costs savings but also longer term strategic benefits. This presentation will address the identification and assessment of these strategic benefits (including increased flexibility, decreased time to market, reduced response time, etc.) for MHS in the semiconductor industry.