937 resultados para Process planning
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Planning is a vital element of project management but it is still not recognized as a process variable. Its objective should be to outperform the initially defined processes, and foresee and overcome possible undesirable events. Detailed task-level master planning is unrealistic since one cannot accurately predict all the requirements and obstacles before work has even started. The process planning methodology (PPM) has thus been developed in order to overcome common problems of the overwhelming project complexity. The essential elements of the PPM are the process planning group (PPG), including a control team that dynamically links the production/site and management, and the planning algorithm embodied within two continuous-improvement loops. The methodology was tested on a factory project in Slovenia and in four successive projects of a similar nature. In addition to a number of improvement ideas and enhanced communication, the applied PPM resulted in 32% higher total productivity, 6% total savings and created a synergistic project environment.
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Mode of access: Internet.
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From a manufacturing perspective, the efficiency of manufacturing operations (such as process planning and production scheduling) are the key element for enhancing manufacturing competence. Process planning and production scheduling functions have been traditionally treated as two separate activities, and have resulted in a range of inefficiencies. These include infeasible process plans, non-available/overloaded resources, high production costs, long production lead times, and so on. Above all, it is unlikely that the dynamic changes can be efficiently dealt with. Despite much research has been conducted to integrate process planning and production scheduling to generate optimised solutions to improve manufacturing efficiency, there is still a gap to achieve the competence required for the current global competitive market. In this research, the concept of multi-agent system (MAS) is adopted as a means to address the aforementioned gap. A MAS consists of a collection of intelligent autonomous agents able to solve complex problems. These agents possess their individual objectives and interact with each other to fulfil the global goal. This paper describes a novel use of an autonomous agent system to facilitate the integration of process planning and production scheduling functions to cope with unpredictable demands, in terms of uncertainties in product mix and demand pattern. The novelty lies with the currency-based iterative agent bidding mechanism to allow process planning and production scheduling options to be evaluated simultaneously, so as to search for an optimised, cost-effective solution. This agent based system aims to achieve manufacturing competence by means of enhancing the flexibility and agility of manufacturing enterprises.
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The thesis describes the work carried out to develop a prototype knowledge-based system 'KBS-SETUPP' to generate process plans for the manufacture of seamless tubes. The work is specifically related to a plant in which hollows are made from solid billets using a rotary piercing process and then reduced to required size and finished properties using the fixed plug cold drawing process. The thesis first discusses various methods of tube production in order to give a general background of tube manufacture. Then a review of the automation of the process planning function is presented in terms of its basic sub-tasks and the techniques and suitability of a knowledge-based system is established. In the light of such a review and a case study, the process planning problem is formulated in the domain of seamless tube manufacture, its basic sub-tasks are identified and capabilities and constraints of the available equipment in the specific plant are established. The task of collecting and collating the process planning knowledge in seamless tube manufacture is discussed and is mostly fulfilled from domain experts, analysing of existing manufacturing records specific to plant, textbooks and applicable Standards. For the cold drawing mill, tube-drawing schedules have been rationalised to correspond with practice. The validation of such schedules has been achieved by computing the process parameters and then comparing these with the drawbench capacity to avoid over-loading. The existing models cannot be simulated in the computer program as such, therefore a mathematical model has been proposed which estimates the process parameters which are in close agreement with experimental values established by other researchers. To implement the concepts, a Knowledge-Based System 'KBS- SETUPP' has been developed on Personal Computer using Turbo- Prolog. The system is capable of generating process plans, production schedules and some additional capabilities to supplement process planning. The system generated process plans have been compared with the actual plans of the company and it has been shown that the results are satisfactory and encouraging and that the system has the capabilities which are useful.
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The manufacture of copper alloy flat rolled metals involves hot and cold rolling operations, together with annealing and other secondary processes, to transform castings (mainly slabs and cakes) into such shapes as strip, plate, sheet, etc. Production is mainly to customer orders in a wide range of specifications for dimensions and properties. However, order quantities are often small and so process planning plays an important role in this industry. Much research work has been done in the past in relation to the technology of flat rolling and the details of the operations, however, there is little or no evidence of any research in the planning of processes for this type of manufacture. Practical observation in a number of rolling mills has established the type of manual process planning traditionally used in this industry. This manual approach, however, has inherent drawbacks, being particularly dependent on the individual planners who gain their knowledge over a long span of practical experience. The introduction of the retrieval CAPP approach to this industry was a first step to reduce these problems. But this could not provide a long-term answer because of the need for an experienced planner to supervise generation of any plan. It also fails to take account of the dynamic nature of the parameters involved in the planning, such as the availability of resources, operation conditions and variations in the costs. The other alternative is the use of a generative approach to planning in the rolling mill context. In this thesis, generative methods are developed for the selection of optimal routes for single orders and then for batches of orders, bearing in mind equipment restrictions, production costs and material yield. The batch order process planning involves the use of a special cluster analysis algorithm for optimal grouping of the orders. This research concentrates on cold-rolling operations. A prototype model of the proposed CAPP system, including both single order and batch order planning options, has been developed and tested on real order data in the industry. The results were satisfactory and compared very favourably with the existing manual and retrieval methods.
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This paper presents the concepts of the intelligent system for aiding of the module assembly technology. The first part of this paper presents a project of intelligent support system for computer aided assembly process planning. The second part includes a coincidence description of the chosen aspects of implementation of this intelligent system using technologies of artificial intelligence (artificial neural networks, fuzzy logic, expert systems and genetic algorithms).
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In the manufacturing industry the term Process Planning (PP) is concerned with determining the sequence of individual manufacturing operations needed to produce a given part or product with a certain machine. In this technical report we propose a preliminary analysis of scientific literature on the topic of process planning for Additive Manufacturing (AM) technologies (i.e. 3D printing). We observe that the process planning for additive manufacturing processes consists of a small set of standard operations (repairing, orientation, supports, slicing and toolpath generation). We analyze each of them in order to emphasize the most critical aspects of the current pipeline as well as highlight the future challenges for this emerging manufacturing technology.
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Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi-jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protégé software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.
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Process planning is a very important industrial activity, since it determines how a part or a product is manufactured. Process planning decisions include machine selection, tool selection, and cutting conditions determination, and thus it is a complex activity. In the presence of unstable demand, flexibility has become a very important characteristic of today's successful industries, for which Flexible Manufacturing Systems (FMSs) have been proposed as a solution. However, we believe that FMS control software is not flexible enough to adapt to different manufacturing system conditions aiming at increasing the system's efficiency. One means to overcome this limitation is to include pre-planned alternatives in the process plan; then planning decisions are made by the control system in real time to select the most appropriate alternative according to the conditions of the shop floor. Some of the advantages of this approach reported in the literature are the reduction of the number of tool setups, and the selection of a replacement machine for executing an operation. To verify whether the presence of alternatives in process plans actually increases the efficiency of the manufacturing system, an investigation was carried out using simulation and design of experiments techniques for alternative plans on a single machine. The proposed methodology and the results are discussed within this paper.
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There is growing international interest in the impact of regulatory controls on the supply of housing The UK has a particularly restrictive planning regime and a detailed and uncertain process of development control linked to it. This paper presents the findings of empirical research on the time taken to gain planning permission for selected recent major housing projects from a sample of local authorities in southern England. The scale of delay found was far greater than is indicated by average official data measuring the extent to which local authorities meet planning delay targets. Hedonic analysis indicated that there is considerable variation in time it takes local authorities to process planning applications, with the worst being four times slower than the best. Smaller builders and housing association developments are processed more quickly than those of large developers and small sites appear to be particularly time intensive. These results suggest that delays in development control may be a significant contributory factor to the low responsiveness of UK housing supply to upturns in market activity.
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There is growing international interest in the impact of regulatory controls on the supply of housing. Most research focuses on the supply impacts of prescribed limits on land use but housing supply may also be affected by the process of planning monitoring and approval but this is hard to measure in detail. The UK has a particularly restrictive planning regime and a detailed and uncertain process of development control linked to it, but does offer the opportunity of detailed site-based investigation of planning delay. This paper presents the findings of empirical research on the time taken to gain planning permission for selected recent major housing projects in southern England. The scale of delay found was far greater than is indicated by average official data measuring the extent to which local authorities meet planning delay targets. Hedonic modelling indicated that there is considerable variation in the time it takes local authorities to process planning applications. Housing association developments are processed more quickly than those of large developers and small sites appear to be particularly time-intensive. These results suggest that delays in development control may be a significant contributory factor to the low responsiveness of UK housing supply to upturns in market activity.
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Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013
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Variations are inherent in all manufacturing processes and can significantly affect the quality of a final assembly, particularly in multistage assembly systems. Existing research in variation management has primarily focused on incorporating GD&T factors into variation propagation models in order to predict product quality and allocate tolerances. However, process induced variation, which has a key influence on process planning, has not been fully studied. Furthermore, the link between variation and cost has not been well established, in particular the effect that assembly process selection has on the final quality and cost of a product. To overcome these barriers, this paper proposes a novel method utilizing process capabilities to establish the relationship between variation and cost. The methodology is discussed using a real industrial case study. The benefits include determining the optimum configuration of an assembly system and facilitating rapid introduction of novel assembly techniques to achieve a competitive edge.