3,026 research outputs found

    Intelligent systems in manufacturing: current developments and future prospects

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    Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

    Energy Efficient Policies, Scheduling, and Design for Sustainable Manufacturing Systems

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    Climate mitigation, more stringent regulations, rising energy costs, and sustainable manufacturing are pushing researchers to focus on energy efficiency, energy flexibility, and implementation of renewable energy sources in manufacturing systems. This thesis aims to analyze the main works proposed regarding these hot topics, and to fill the gaps in the literature. First, a detailed literature review is proposed. Works regarding energy efficiency in different manufacturing levels, in the assembly line, energy saving policies, and the implementation of renewable energy sources are analyzed. Then, trying to fill the gaps in the literature, different topics are analyzed more in depth. In the single machine context, a mathematical model aiming to align the manufacturing power required to a renewable energy supply in order to obtain the maximum profit is developed. The model is applied to a single work center powered by the electric grid and by a photovoltaic system; afterwards, energy storage is also added to the power system. Analyzing the job shop context, switch off policies implementing workload approach and scheduling considering variable speed of the machines and power constraints are proposed. The direct and indirect workloads of the machines are considered to support the switch on/off decisions. A simulation model is developed to test the proposed policies compared to others presented in the literature. Regarding the job shop scheduling, a fixed and variable power constraints are considered, assuming the minimization of the makespan as the objective function. Studying the factory level, a mathematical model to design a flow line considering the possibility of using switch-off policies is developed. The design model for production lines includes a targeted imbalance among the workstations to allow for defined idle time. Finally, the main findings, results, and the future directions and challenges are presented

    Capacity Planning and Leadtime management

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    In this paper we discuss a framework for capacity planning and lead time management in manufacturing companies, with an emphasis on the machine shop. First we show how queueing models can be used to find approximations of the mean and the variance of manufacturing shop lead times. These quantities often serve as a basis to set a fixed planned lead time in an MRP-controlled environment. A major drawback of a fixed planned lead time is the ignorance of the correlation between actual work loads and the lead times that can be realized under a limited capacity flexibility. To overcome this problem, we develop a method that determines the earliest possible completion time of any arriving job, without sacrificing the delivery performance of any other job in the shop. This earliest completion time is then taken to be the delivery date and thereby determines a workload-dependent planned lead time. We compare this capacity planning procedure with a fixed planned lead time approach (as in MRP), with a procedure in which lead times are estimated based on the amount of work in the shop, and with a workload-oriented release procedure. Numerical experiments so far show an excellent performance of the capacity planning procedure

    Aggregate Cost Model for Scalability in Manufacturing Systems

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    Manufacturing continues to face escalated cost challenges on a global scale. To gain a competitive advantage among their rivals, manufacturing firms continuously strive to lower their manufacturing costs than their competitors. This dissertation introduces mathematical optimization model based on an Activity-Based Costing (ABC) method, which considers the relationship between hourly rates and annual hours on each machine/workcentre. Several constraints are considered in the proposed models, such as the cost of reconfiguration, capacity, available machining hours, a decision on facility expansion and a cost-benefit analysis on industry 4.0 implementation. The model outputs are the optimum hourly rates, deciding which jobs to accept or reject, and determining reconfiguration\u27s financial feasibility. Reconfiguration in this dissertation describes system-level reconfiguration (investing in additional equipment/machinery) and/or machine-level reconfiguration (extra module to a piece of existing equipment) as well as factory-level (in terms of expanding additional factory segments to the existing facility). The model will be applied to a real-life case study of a global original equipment manufacturer (OEM) of machinery. The mathematical models proposed in this dissertation are developed based on a multinational hydraulic-press manufacturing company. The company owns a local machine shop (one of the sister companies in North America) for building hydraulic presses meant to be delivered to companies producing engineered wood products (such as OSB (oriented Strand Board), PB (Particle Board), and MDF Board (Medium-Density Fibre) …etc.). The sister company in North America occupies a footprint of 5,000 meters squared with a number of capabilities such as machining (turning and machining centres, welding, assembly, material handling…etc.). Several aspects of the model proposed in this dissertation had been implemented in the company such as the bi-directional relationship between total hours and hourly rates which assisted the company in gaining more jobs and projects. In addition, connectivity between strategic suppliers and company branched has been established (enabler of Industry 4.0). The proposed model\u27s novelty incorporates the bi-directional relationship between hourly rates and annual hours in each workcentre. It provides a managerial decision-making tool for the investment level required to pursue new business and gaining a competitive advantage over rivals. Furthermore, a cost-benefit analysis is performed on the implementation of Industry 4.0. The primary aspect considered in industry 4.0 is Information Communication Technology (ICT) infrastructure with strategic suppliers to intensify interconnection between the manufacturing firm and the strategic suppliers. This research\u27s significance is focused on cost analysis and provides managers in manufacturing facilities with the required decision-making tools to decide on orders to accept or decline, as well as investing in additional production equipment, facility expansion, as well as Industry 4.0. In addition, this research will also help manufacturing companies achieve a competitive edge among rivals by reducing hourly rates within their facility. Furthermore, the implementation of the model reduced hourly rates for workcentres by up to 25% as a result of accepting more jobs (and accordingly, machining hours) on the available workcentres, and hence, reducing the hourly rates. This implementation has helped the company gain a competitive advantage among rivals since pricing of products submitted to customer was reduced. Additional benefits and significance are (1) providing manufacturing companies with a method to quantify the decision-making process for right-sizing their manufacturing space, (2) the ability to justify growing a scalable system (machine level, system-level and factory level) using costing (not customer demand), (3) expanding market share and, (4) reducing operational cost and allowing companies a numerical model to justify scaling the manufacturing system

    Process assessment for the extended enterprise during early product development using novel computational techniques

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    Manufacturing practices have evolved over the last quarter of a century in the light of changes to manufacturing technology and demand. To sustain this growth companies are increasingly focused on better design and quicker time to market, to stay one step ahead of the competition. Expanding technology capabilities have included microcomputers and telecommunications. In particular the Internet has allowed businesses to trade with an extended customer base, resulting in a greater demand and perpetuating the cycle. To mirror this statement, businesses are looking increasingly far and wide for suitable suppliers. This work identifies a need in the market for an Internet based supplier selection function, during early product development. The development of this work differs significantly from other process selection methods by the use of the Internet to link companies. It has advantages for product development relating to the scope of the opportunities, diversity of possible manufacturing operations and rapid assessment of processes. In particular the system can be broken down into two main functions. Process Selection (PS) and Factory Selection (FS). The PS method presented enables many processes to be modelled, in multiple organisations for a single product. The Internet is used to gain access to supplier facilities by adopting the same principles as on-line banking, or shopping, for data input and access. The results of these assessments are retained by the system for later analysis. The FS method utilises this data to model and compare supplier attributes, allowing the user to manipulate the data to fit their requirements. Testing of the system has proved encouraging for many operations, including Injection Moulding and CNC Machining. It can be concluded that the identification of manufacturing operations outside the remit of companies' normal scope will create further opportunities for supplier integration

    Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

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    Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

    An investigation into tooling requirements and strategies for FMS operation

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    A study of the minimum tooling requirements and strategies for efficient operation of Flexible Manufacturing Systems, FMS's, in Assembly set Production, ASP, i.e production in sets of parts to completely assemble one or more product units, is presented in this research work. The main investigating tool is a simulation model. With this model the tool groups to be loaded into machines and fixtured pallet requirements were studied in conjunction with two scheduling rules. One is a FCFS rule and the other is a new rule, called MRPAS, which schedules work on the basis of the number of parts still unfinished belonging to an Assembly Set. The results of the research work show that ASP can be efficiently carried out in FMS's. However this requires that a good system set-up and adequate operating strategies are used. In particular appropriate tooling levels and good tooling configurations,TC's, i.e. combinations of tools in groups to be loaded into the machines, must be established to achieve high FMS performance. Tooling combination and duplication heuristic rules and the simulation model can be used for achieving this aim. The heuristic approach is shown to be necessary due to the impossibility, in a reasonable time, of evaluating the performance of FMS's under the large number of alternative tooling configurations which are possible. The level of fixtured pallets used can also have a great influence on system performance. Appropriate levels of these resources to operate FMS's for given TC's can be established using the methodology developed in this work. It is also important that good scheduling rules are used. In the cases studied, the MRPAS rule produces the best performance expressed as the combination of FMS utilization and production of complete assembly sets. Moreover a very small assembly set batch size, ASBS, i.e. number of AS released together into the FMS, is likely to be preferable. In the cases studied an ASBS of one performed best overall

    Robust production planning and control for multi-stage systems with flexible final assembly lines

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    Production planning of final assembly systems is a challenging task, as the often fluctuating order volumes require flexible solutions. Besides, the calculated plans need to be robust against the process-level disturbances and stochastic nature of some parameters like manual processing times or machine availability. In the paper, a simulation-based optimisation method is proposed that utilises lower level shop floor data to calculate robust production plans for final assembly lines of a flexible, multi-stage production system. In order to minimise the idle times when executing the plans, the capacity control that specifies the proper operatorâtask assignments is also determined. The analysed multi-stage system is operated with a pull strategy, which means that the production at the final assembly lines generates demands for the preceding stages providing the assembled components

    Tool flow management in batch manufacturing systems for cylindrical components

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    The objective of the research is to study the design of and operating strategies for advanced tool flow systems in highly automated turning systems. A prototype workstation has been built to aid this process. The thesis consists of three main parts. In the first part the current flexible manufacturing technology is reviewed with emphasis laid on tool flow and production scheduling problems. The 'State-of-the-Art' turning systems are studied, to highlight the requirement of the computer modelling of tool flow systems. In the second part, the design of a computer model using fast modelling algorithms is reported. The model design has concentrated on the tool flow system performance forecasting and improving. Attention has been given to the full representation of highly automatic features evident in turning systems. A number of contemporary production scheduling rules have been incorporated into the computer model structure, with the objectives of providing a frontend to the tool flow model, and to examine the tool flow problems interactively with the production scheduling rules. The user-interface of the model employs conversational type screens for tool flow network specification and data handling, which enhances its user friendliness greatly. An effective, fast, and easy to handle data base management system for tool, part, machine data entries has been· built up to facilitate the model performance. The third part of the thesis is concerned with the validation and application of the model with industry supplied data to examine system performance, and to evaluate alternative strategies. Conclusions drawn from this research and the recommendations for further work are finally indicated

    A manufacturing planning and control system for a flexible manufacturing system

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    A flexible manufacturing system (FMS) can offer important advantages in terms of more efficient production, shorter throughput times, lower stocks and a higher quality of work. To realize these advantages, a well designed manufacturing planning and control system (MPCS) is a key condition. In practical cases, these planning and control systems are often based on a hierarchical structure. This paper discusses the most relevant characteristics of such a hierarchical MPCS and, by using a practical case, describes possible solutions to a variety of subproblems
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