A hybrid Hopfield network-genetic algorithm approach to optimal process plan selection

In the automated manufacturing environment, different sets of alternative process plans can normally be generated to manufacture each part. However, this entails considerable complexities in solving the process plan selection problem because each of these process plans demands specification of their individual and varying manufacturing costs and manufacturing resource requirements, such as machines, fixtures/jigs, and cutting tools. In this paper the problem of selecting exactly one representative from a set of alternative process plans for each part is formulated. The purpose is to minimize, for all the parts to be manufactured, the sum of both the costs of the selected process plans and the dissimilarities in their manufacturing resource requirements. The techniques of Hopfield neural network and genetic algorithm are introduced as possible approaches to solve such a problem. In particular, a hybrid Hopfield network-genetic algorithm approach is also proposed in this paper as an effective near-global optimization technique to provide a good quality solution to the process plan selection problem. The effectiveness of the proposed hybrid approach is illustrated by comparing its performance with that of some published approaches and other optimization techniques, by using several examples currently available in the literature, as well as a few randomly generated examples.     

Process plan selection

Process planning is the task of generating a plan for transforming raw material to its finished form according to design specifications. The existence of alternative feasible process plans for a part and the manufacture of several parts in a single facility sharing constrained resources, makes careful selection of process plans essential. This paper formalizes the selection of process plans with the objective of minimizing the total processing time and the total number of processing steps. The set of plans are then consolidated to minimize the resources used. This is accompanied by intangible benefits such as simplified planning and scheduling, fewer constraints on designing the layout, and an overall reduction in the manufacturing cost. As a word of caution, it may be added that process plans have wide ranging impact on factory operations and it is unrealistic to expect a single model to be comprehensive in addressing the problem. The model outlined in the paper highlights the key issues and provides an analytical basis for selecting process plans.     

An integrated approach to solving the process plan selection problem in an automated manufacturing system

Selection of a process plan is a crucial decision making problem encountered in manufacturing systems due to the presence of several alternative process plans arising out of availability of several machines, tools, fixtures etc. capable of performing the same operations of the part. Because of its vital impact on the performance of the manufacturing system, several researchers have addressed the plan selection problem in recent years. Although functional integration plays a significant role in the development of current manufacturing systems, many of the functions in manufacturing systems have been developed without a sense of integration. Therefore, it becomes important to emphasize the integration of functions rather than the individual development of the function itself. This paper attempts to address the plan selection problem taking into account the similarity measures among the process plans of the parts. Four algorithms have been developed to integrate the several segments of the process plan selection problem. Application of these algorithms ensures considerable computational simplicity in yielding the feasible process plans of the parts.     

Integration of process planning and scheduling by exploring the flexibility of process planning

A unique method for the integration of process planning and scheduling in a batch-manufacturing environment is reported. This integration is essential for the optimum use of production resources and for the generation of realistic process plans that can be readily executed with little modification. The integration problem is modelled at two levels: process planning and scheduling, which are linked by an intelligent facilitator. The process-planning module employs an optimization approach in which the whole plan solution space in terms of available machines, tools, tool accessibility and precedence constraints is first generated and a search algorithm is then used to find the optimal plan. For a given set of jobs, the scheduling module takes the optimal plans for each job and generates a schedule based on a given criterion, as well as the performance parameters (machine utilization and number of tardy jobs). An unsatisfied performance parameter is fed back to the facilitator, which then identifies a particular job and issues a change to its process plan solution space. The iteration of process Planning -scheduling-solution space modification continues until a schedule is satisfactory or until no further improvement can be made. The uniqueness of this approach is characterized by the flexibility of the process-planning strategy and the intelligent facilitator, which makes full use of the plan solution space intuitively to reach a satisfactory schedule. (It may not be the optimal, though.) The integrated system was implemented in the manufacturing of prismatic parts. The testing results show that the developed integration method can achieve satisfactory process plans and a schedule in an effective and efficient manner.     

A manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation for aircraft structural parts

Manufacturing of aircraft structural parts has the characteristics of multiple varieties, complex structures and small batches, which make the manufacturing resource allocation highly difficult. This paper proposes a manufacturing resource allocation method with knowledge-based fuzzy comprehensive evaluation, considering multiple manufacturing resources including process planners, machine tools and cutting tools, as well as manufacturing process schemes of aircraft structural parts. Knowledge in terms of experts’ experience and historical data is used for fuzzy comprehensive evaluation. A manufacturing resource allocation model is proposed based on the analysis of manufacturing processes of aircraft structural parts. The capability of planners, the complexity of structural parts, the reliability of machine tools, the reliability of cutting tools and the correlations between manufacturing resources and structural parts are evaluated using the fuzzy comprehensive evaluation method. Multiple manufacturing resources are allocated based on the fuzzy comprehensive evaluation results. A prototype system has been implemented and a case study is used to validate the proposed approach.     

A process planning-orientated approach to part family formation problem in group technology applications

The paper reports on constrained hierarchical clustering applied to similarity analysis, the grouping of process plans and, consequently, the parts manufactured in accordance with them. It proposes solutions to some important problems such as: determining a metric of process plan similarity evaluation; the study of a cluster-creating technique with two process plans and a rule for singling out the standard plan; the determination of a logical threshold value for partitioning into families. Validation of the method creates a family set. The ‘strong forms’ of this set constitute definitive partition into families of the process plan set.     

A multi-criteria decision-making approach for capacity allocation problem in semiconductor fabrication

In today's highly competitive environment, good customer relationship management is essential for a company to survive and to acquire reasonable profit. A semiconductor enterprise has multi-site fabs, and follows basically a make-to-order production type. The allocation of capacity for manufacturing different types of products is important for the competitiveness and future development of the enterprise. To cope with this requirement, a multi-criteria decision-making approach is proposed in this article for more efficient evaluation and selection of capacity allocation plans in semiconductor fabs. Under this approach, fuzzy analytic network process (FANP) is incorporated with fuzzy Delphi method (FDM), constraint programming (CP) and benefits, opportunities, costs and risks (BOCR). FDM is used to achieve a consensus among the opinions of experts. CP is used to screen out a set of capacity allocation plans that should be further evaluated. FANP with BOCR is used to evaluate the various factors and the interrelationship among the factors under the BOCR merits and to determine the expected performance of the capacity allocation plans. The proposed approach can provide a ranking and also priorities of different capacity allocation plans, and the fab can select the most appropriate capacity allocation for production in the case that insufficient capacity existed.     

A proposal of cost-tolerance models directly collected from the manufacturing process

In this paper, the concept of cost-tolerance functions based on data directly obtained from the manufacturing process is proposed. Traditional models used in manufacturing field define cost-tolerance relationships from mathematical functions whose relationship with the process is not usually set in a clear way. In this work, proposed models allow to obtain cost-tolerance functions directly from parameters measured on manufacturing process. The paper defines some of these functions using statistical distributions derived from the population of manufactured parts. A general methodology to reach a cost-tolerance function from any distribution of the manufactured parts is proposed. Once functions are defined, an application example is presented. Finally, the main criteria for suitable appropriateness use of models are established.     

Improving the performances of part dispatching based on multiple process plans using graph theory

An intrinsic characteristic for manufacturing a part is the existence of diverse processing routes. In this paper, we deal with the improvement of part dispatching performance based on the availability of multiple process plans of a machined part. Procedures to represent multiple process plans with a graphic representation are developed so as to facilitate the utilization of process plans. We propose a simulation model to test the impacts of multiple process plans on the performances of real time scheduling. The study shows that by applying the simulation model to multiple processes in the manufacturing of machined parts, the flexibility of the manufacturing system can be increased; the total production flow time can be reduced; and the efficient utilization of production resources is improved.     

FMS中CAPP与CAM集成技术的研究

介绍了一个适用于FMS的CAPP／CAM集成系统。它由创成法CAPP系统，NC自动编程系统和它们之间的接口等主要部分组成。系统采用基于特征的零件描述方法作为集成环境下统一的零件信息模型。由CAPP系统生成的工艺规程，通过接口文件自动传输给NC编程系统，经过特征识别后，从特征NC程序库中调用相应的特征数控程序，实现NC自动编程，为检验NC程序的错误，系统还具有刀具轨迹仿真功能，系统用户界面友好，经加工验证，可用于生产。     

Optimization of process plans using a constraint-based tabu search approach

A computer-aided process planning system should ideally generate and optimize process plans to ensure the application of good manufacturing practices and maintain the consistency of the desired functional specifications of a part during its production processes. Crucial processes, such as selecting machining resources, determining set-up plans and sequencing operations of a part should be considered simultaneously to achieve global optimal solutions. In this paper, these processes are integrated and modelled as a constraint-based optimization problem, and a tabu search-based approach is proposed to solve it effectively. In the optimization model, costs of the utilized machines and cutting tools, machine changes, tool changes, set-ups and departure from good manufacturing practices (penalty function) are the optimization evaluation criteria. Precedence constraints from the geometric and manufacturing interactions between features and their related operations in a part are defined and classified according to their effects on the plan feasibility and processing quality. A hybrid constraint-handling method is developed and embedded in the optimization algorithm to conduct the search efficiently in a large-size constraint-based space. Case studies, which are used for comparing this approach with the genetic algorithm and simulated annealing approaches, and the proposed constraint-handling method and other constraint methods, are discussed to highlight the performance of this approach in terms of the solution quality and computational efficiency of the algorithm.     

An integrated fuzzy approach for the selection of outsourcing manufacturing partners in pharmaceutical R&D

The selection of the outsourcing manufacturing partners (OMPs) is an important issue for research and development (R&D) in the pharmaceutical industry. The selection process considers several main criteria, as well as a few sub-criteria for each main criterion. Such problems can be formulated as hierarchical structures and can usually be resolved with multi-criteria decision-making approaches. This paper presents an integrated fuzzy approach for selecting a suitable OMP in pharmaceutical R&D. In the integrated approach, fuzzy concepts are used for decision-makers’ subjective judgments to reflect the vague nature of the selection process. Fuzzy AHP and fuzzy TOPSIS are included in the integrated approach. Fuzzy AHP is used to determine the fuzzy weights of criteria and sub-criteria because it can effectively determine various criteria's weights in a hierarchical structure. Fuzzy TOPSIS aims to find the OMP with the best performance with respect to the sub-criteria. We exemplify the integrated approach using a numerical application to demonstrate its feasibility.     

A fuzzy approach to multi-objective routing problem with applications to process planning in manufacturing systems

In this paper a method is developed for the selection of an efficient path in a fuzzy multi-objective network. The application of the methodology developed is illustrated by a process plan selection problem in a manufacturing environment.     

An intelligent process planning system for micro turn-mill parts

An attempt has been made to develop a generalised system for the generation of process plan for the manufacture of micro parts in this work. It has two components; first one deals with automatic part feature extraction from feature-based model and second one performs the execution of process planning activities in accordance with feature using knowledge-based system approach. The proposed system maps extensible markup language (XML) data for the feature based-model and produces the corresponding manufacturing activities needed for the manufacture of micro parts. The process plan modules considered in this work includes process sequence, tools and fixtures, process parameters selection and set-up plan generation. An attempt has been made to develop process parameters selection module based on experimental investigation and optimisation apart from manufacturing catalogues and user manuals. Feature extraction through XML files avoids complex feature extraction process. The application of the developed system has been verified with a case study. The present system is limited to micro turn-mill features. Incorporation of more micro features and consideration of other activities of process plan ensures a complete process planning system for micro-machining processes.     

An implicit enumeration approach to probabilistic tolerance allocation under conventional tolerance control

The accuracy and precision of a manufactured dimension is largely dependent on the accuracy and precision of the technological processes selected for its execution. It is not unusual to have available several competing technological processes for execution of each manufacturing operation specified in a process plan, where it is generally assumed that, as the precision of the technological process improves, the associated cost and yield of the operation increase. This paper presents an implicit enumeration approach to the selection of an optimum subset of technological processes required to execute a process plan under a conventional tolerance control strategy. A probabilistic approach to the problem is presented and the First Order Second Moment Method (FOSMM) is used to estimate yield for an interdependent system of functional requirements.     

Intelligent layout planning for rapid prototyping

Significant savings in cost and time can be achieved in rapid prototyping (RP) by manufacturing multiple parts in a single setup to achieve efficient machine volume utilization. This paper reports the design and implementation of a system for the optimal layout planning of 3D parts for a RP process. A genetic algorithm (GA) based search strategy has been used to arrive at a good packing layout for a chosen set of parts and RP process. A two stage approach has been proposed to initially short-list acceptable orientations for each part followed by the search for a layout plan which optimizes in terms of final product quality and build time. The GA uses a hybrid objective function comprising of the weighted measures like part build height, staircase effect, volume and area-of-contact of support structures. In essence it captures the key metrics of efficiency and goodness of packing for RP. The final layout plan is produced in the form of a composite part CAD model which can be directly exported to a RP machine for manufacturing. Design methodology of the system has been presented with some representative case studies.     

Process plan selection based on product mix and production volume

Most shops currently maintain a single process plan for each part type manufactured by the shop even when multiple process plans are feasible to produce the part. The use of a static process plan for a part regardless of the product mix and volume robs the shop of production flexibility and efficiency. In this paper, given that multiple process plans for a part exist, a method to determine the best process plan to implement for a part type in a given production scenario defined by a known product mix and volume is addressed. The method selects a set of process plans to implement based on minimizing total material handling and machining time for the part mix and volume. The problem is modelled mathematically and solved using a heuristic algorithm. Experimental results to describe the performance of the algorithm are presented for different production scenarios, problem sizes, and solution strategies.     

Evaluating the manufacturability of machined parts and their setup plans

Design-for-manufacturability is an approach that requires product designers to consider the manufacturing issues of a product concurrently with the geometrical and design aspects. This paper presents a manufacturability evaluation methodology that incorporates design, machining and work-holding issues. The evaluation is carried out in two parts. The first part is related to the machinability of the features of the part, whereas the second part is concerned about the fixturability of the part with regards to its planar faces. The methodology uses the fuzzy sets theory and the analytical hierarchy process method to evaluate the accessibility, orientation, dimensional tolerances, and surface finish specifications of a part. The former is used to model the various ill-defined boundaries of the criteria, while the latter allows for differences in opinions from designers/machinists to be incorporated into the evaluation process. The quantitative machinability and fixturability indices found can be used to evaluate designs and generate redesign suggestions. A setup plans evaluation module has been developed to determine the merit indices of setup plans for machining a part using these machinability and fixturability indices.     

云制造环境下板材余料资源的服务匹配方法

在云制造环境下,针对中小型企业加工后的板材余料造成极大资源浪费的问题,提出了一种基于语义相似度算法同时融入QoS(quality of service,服务质量)信息的分层次资源描述模型.首先,建立板材余料和板材加工设备资源的本体模型;然后,基于语义相似度算法对板材余料和板材加工设备的各个属性参数进行匹配,得到初选服务...