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A case study for this project is performed at Autoliv in Thailand the company uses a lean production flow approach. This manufacturing plant operates on the level of Industry 3.0, which automates processes using information technology. The case study scenario in manufacturing plants that runs in industrial automation 3.0 has some problems in material handling under the logistics division. By implementing AGV (Automated Guided Vehicle) with help of simulation, the time reduction factor through route and time optimization can be processed and displayed. This will have a direct impact on increasing the material handling efficiency in the production plant. The simulation used for AGV in plant layout is Discrete Event Simulation (DES), which divides each event according to its time. Siemens’s Tecnomatix Plant Simulation software is used as a software. This software handles complex production systems and provides control methods. In this thesis work, the entire plant is implemented in the simulated environment based on the plant layout as per dimensions. Then the AGV routing is done from source to destination. The stations are made as per the requirements between the source and the destination for loading from/ unloading to AGV. The processing time of these stations is given as inputs and the simulation is run for a shift to get the throughput. The specification of the AGV such as speed and dimensions given in the simulated environment is taken from the case study of AGV. A total of 55 AGV models’ are studied and 40 of them are selected for this particular plant layout, they are selected based on their features along with the throughput of units transferred from source to destination. The parameters of the AGV are based on the case study of AGV models. The unit throughput acquired in the simulated environment by the AGV is 20% to 22.5% more efficient than manual material handling.

The Vehicle Routing Problem with Time Windows (VRPTW) is an important and computationally hard optimization problem frequently encountered in Scheduling and logistics. The Vehicle Routing Problem (VRP) can be described as the problem of designing the most efficient and economical routes from one depot to a set of customers using a limited number of vehicles. This research addresses the VRPTW under the following additional complicating features that are often encountered in practical problems: 1. Customers have strict time windows for receiving a vehicle, i.e., vehicles are not allowed to arrive at the customer’s location earlier than the lower limit of the specified time window, which is relaxed in previous research work. 2. There is a limited number of loading/unloading docks for dispatching/receiving the vehicles at the depot The main goal of this research is to propose a framework for solving the VRPTW with the constraints stated above by generating near-optimal routes for the vehicles so as to minimize the total traveling distance. First, the proposed framework clusters customers into groups based on their proximity to each other. Second, a Probabilistic Route Generation (PRG) algorithm is applied to each cluster to find the best route for visiting customers by each vehicle; multiple routes per vehicle are generated and each route is associated with a set of feasible dispatching times from the depot. Third, an assignment problem formulation determines the best dispatching time and route for each vehicle that minimizes the total traveling distance. iii The proposed algorithm is tested on a set of benchmark problems that were originally developed by Marius M. Solomon and the results indicate that the algorithm works well with about 1.14% average deviation from the best-known solutions. The benchmark problems are then modified by adjusting some of the customer time window limits, and adding the staggered vehicle dispatching constraint. For demonstration purposes, the proposed clustering and PRG algorithms are then applied to the modified benchmark problems.

The design, simulation and evaluation of an intelligent and integrated load management system is presented in this dissertation. The objective of this research was to apply modern computer and communication technology to influence customer use of electricity in ways that would produce desired changes in the utility's load shape. Peak clipping (reduction of peak load) using direct load control is the primary application of this research. The prototype computerized communication and control package developed during this work has demonstrated the feasibility of this concept. The load management system consists of a network of computers, data and graphics terminals, controllers, modems and other communication hardware, and the necessary software. The network of interactive computers divides the responsibility of monitoring of meteorological data, electric load, and performing other functions. These functions include: data collection, processing and archiving, load forecasting, load modeling, information display and alarm processing. Each of these functions requires a certain amount of intelligence depending on the sophistication and complication of that function. Also, a high level of reliability has been provided to each function to guarantee an uninterrupted operation of the system. A full scale simulation of this concept was carried out in the laboratory using five microcomputers and the necessary communication hardware. An important and integral part of the research effort is the development of the short-term load forecast, load models and the decision support system using rule-based algorithms and expert systems. Each of these functions has shown the ability to produce more accurate results compared to classical techniques while at the same time requiring much less computing time and historical data. Development of these functions has made the use of microcomputers for constructing an integrated load management system possible and practical. Also, these functions can be applied for other applications in the electric utility industry and maintain their importance and contribution. In addition to that, the use of rule-based algorithms and expert systems promises to yield significant benefits in using microcomputers in the load management area. / Ph. D.

This contribution discusses a new control concept (compare Boden et al., 2021) that allows transport load exchange in hybrid AMHS. It focuses on vehicles able to perform load exchange dynamically by splitting transport requests into sub-tasks determined ad-hoc depending on the current system status. Unlike conventional control approaches for hybrid AMHS, our dispatching approach does not rely on high-level control rules which statically split transport tasks in advance.

Photolithography is the most complex of the operations involved in the fabrication of a wafer, and it requires the greatest precision. Photolithography is used to create multiple layers of circuit patterns on a chip. Traditionally, wafer fab operations, and in particular, those performed in the photolithography processing area, have always presented challenging scheduling and control problems. Some of the characteristics that make the photolithography processing area difficult to schedule are as follows: reentrant flow, unpredictable yield and rework time at critical operations, shared resources such as reticles, rapidly changing technologies, and lot dedication for steppers and scanners for critical layers. This processing area, where wafers are exposed using scanners or steppers, typically, comprises the bottleneck workstations. Also, the numbers of reticles available for a given layer of product type are limited. Consequently, it is important to develop appropriate schedules to ensure effective utilization of the tools involved. In this study, a manufacturing line that is used to produce four dynamic random access memory (DRAM) products, requiring approximately 240 stages with 18 photolithography layers, is considered. The problem we propose to investigate can concisely be described as follows: Given a set of products to be processed in a photolithography area consisting of steppers and scanners (tools), with each product requiring a specific reticle type, determine the sequence in which to process the lots on the tools loaded with requisite reticles, so as to minimize the cycle time. The reticles required for processing a product are known apriori and can be transferred from one tool to another. Also, the lot dedication requirement has to be met. This requirement pertains to the fact that some of the layers of a lot should be processed on the same tool. (Scanner or Stepper). The processing of other layers may not require lot dedication. These are handled accordingly. Some lots may enter into the system with the requirement of processing them urgently. (called hot lots). These are handled in the formulation of the problem as such. Two solution methodologies are presented for the above stated problem. The first methodology uses a mathematical programming based approach. For the given routes and processing times of the product types, the entire problem is formulated as an Integer program. This integer program uses the start time of the jobs at various operations and the availability of reticles as variables, among others. The objective is to reduce the cycle time of the lots released into the system. The cycle time of a lot is defined as the time that a lot spends in the system. Results from the experimentation for integer program show that the computation time for solving small size problems is very high. A methodology is presented to solve this model efficiently. The second methodology consists of the development of a new dispatching rule for scheduling lots in the photolithography processing area. This along with the other dispatching rules discussed in the literature are implemented using the Autosched AP software to study the impact that lot dedication makes on the performance of a fab. The performance measures that are considered include throughput, cycle time, WIP and utilization of tool sets. The results are presented for 1-level, 2-level and 3-level lot dedication schemes. . It is shown that the 3- level lot dedication scheme performs the best under no preventive maintenance/breakdown case while, for the deterministic value of unscheduled breakdown times and preventive maintenance schedule used, 1-level lot dedication performed the best. Even though the 3-level lot dedication scheme is more flexible as compared to the 1–level lot dedication scheme, yet for the values of unscheduled breakdown times and preventive maintenance schedule used, the performance of the 3- level lot dedication scheme is worse than that of the 1- level lot dedication scheme. For another set of break down time values and preventive maintenance schedule, the outcome can be different. We also compare the performance of the proposed procedure with that of the dispatching rules available with the AutoSched AP software. The results indicate that the proposed procedure is consistent in generating better solutions under different operating conditions. / Master of Science

Most of the techniques that have been applied to the short-term load forecasting problem fall within the time series approaches. The exception to this has been a new approach based on the application of expert systems. Recently several techniques have been reported which apply the rule-based (or expert systems) approach to the short-term load forecasting problem. However, the maximum lead time used for these forecasts has not gone beyond 48 hours, even though there is a significant difference between these algorithms in terms of their data base requirements (few weeks to 10 years). The work reported in this dissertation deals with two aspects. The first one is the application of rule-based techniques to weekly load forecast. A rule-based technique is presented that is capable of issuing a 168-hour lead-time load forecast. The second aspect is the development of a comprehensive load forecasting system that utilizes both the statistical and rule-based approaches. This integration overcomes the deficiencies that exist in both of these modeling techniques. The load forecasting technique is developed using two parallel approaches. In the first approach expert information is used to identify weather variables, day types and diurnal effects that influence the electrical utility load. These parameters and hourly historical loads are then selectively used for various statistical techniques (e.g., univariate, transfer function and linear regression). A weighted average load forecast is then produced which judiciously combines the forecasts from these three techniques. The second approach, however, is free of any significant statistical computation, and is based totally on rules derived from electric utility experts. The data base requirement for any of these approaches do not extend more than four weeks ol hourly load, dry bulb and dew point temperatures. When the algorithms are applied to generate seven-day ahead load forecasts for summer (August) and winter (February) the average forecast errors for the month come under 3%. / Ph. D.

Direct Load Control (DLC) -- the direct control of customer loads by an electric utility for the economic and reliable operation of the power system, is an important and active element of Load Management (LM). Currently attention has focussed on the integration of DLC into system operations. However, as yet, DLC is regarded as a discretionary resource to be used by the system operator based on informed judgment. The integration process has therefore, concentrated on improving the informational inputs to the operator. This dissertation extends the integration from that of a discretionary resource to a dispatchable system resource. The concept of the dynamic dispatch of DLC is formulated and defined to be an online evaluation and utilization of DLC for optimum benefit to the utility, as system conditions change. The concept envisages the use of DLC in an automated mode and coordinated with other system resources for optimum benefit. An important and integral part of the research effort is the development of a cost characterization of DLC. A closed form solution, using a dynamic programming framework, has been developed to estimate the costs of DLC dispatch. The derivation takes into account all operational constraints on the utilization of DLC -- payback characteristics, maximum on-times and minimum recovery times. The cost, defined as the difference in the fuel costs with and without DLC dispatch, were found to be dependent on the cost characteristics of the online generators and the load shape impacts of DLC dispatch. The dynamic dispatch concept is concretized by a power system operations model which incorporates DLC dispatch for fuel cost minimization and peak load shaving. The two modes are toggled by the dispatch algorithm as system conditions change. Results from the model are presented for several combinations of system conditions and DLC system parameters. / Ph. D.

This work explores the need for multiprocessing in the power industry. A suitable computer architecture for power system problems is presented. An efficient decomposition technique is developed to solve the problem parallely. Simulation of distributed processing using IBM 370 computer is considered. A microprocessor version of load flow program is developed and distributed load flow for on-line and off-line applications are studied. A novel algorithm for economic dispatch with and without transmission losses is presented. The algorithm utilizes a closed form expression for the calculation of the Lagrange multiplier thereby avoiding any iterative process in the calculation. Different nonlinear programming techniques are compared to the improved method. The algorithm presented is fast and appears to have good convergence properties. The improved algorithm is extended to distributed processing. Characteristics of a distributed microcomputer system and a multiple processor system are discussed. Intel 8080, 8085 and 8086 versions of distributed and multiprocessing methods are presented to solve power system problems. / Ph. D.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering in the School of Electrical and Information Engineering, July 2017 / This dissertation presents the design and testing of controllers intended to provide au- tonomous demand response, through the use of water heater loads and grid frequency measurements. The controllers use measured frequency as an indication of the strain on a utility grid, which allows demand side management to be isolated from any form of central control. Water heaters can operate as exible loads because their power consump- tion can be dispatched or deferred without directly impacting users. These properties make it possible to control individual water heaters based on the functioning of the grid, rather than end user input. The purpose of this research is to ultimately provide a low- cost alternative to a traditional Smart Grid, that will improve the resilience of a grid without negatively impacting users. The controllers presented here focus on ensuring that users receive hot water, while attempting to reduce any imbalance between power generated and power consumed on the grid. Simulations of these controllers in various situations highlight that while the controllers developed respond suitably to variations in the grid frequency and adequately ensure end users receive hot water, the practical bene t of the controllers depends largely on the intrinsic characteristics of the grid. / CK2018