摘要:

We consider the optimal allocation of buffer storage spaces in unpaced production lines with variable processing times. It is known that for a fixed total number of buffer spaces, the production rate can often be improved by deliberately unbalancing the buffer allocations in an inverted bowl pattern (the “storage bowl phenomenon”), with more storage space allocated to the internal stations than to the end stations. It has been hypothesized that if the total number of buffer spaces is also a decision variable, then for a reasonable cost model the optimal allocation would have one additional storage space at each of the internal stations. This paper uses a cost modeltoshow that the optimal allocationismore complicated than this. For balanced lines, the invertedbowlpatternistypically optimal, but the bowl shape becomes more and more pronounced (in an absolute sense) with larger numbers of buffer spaces. However, the relative shape of the bowl stays fairly constant. However, if the workloadisunbalanced, the buffer space pattern deviates from the bowl pattern by reducing the numberofbuffer spaces in buffers that are not adjacent to the bottleneck machine.

ISSN:0740-817X    

DOI:10.1080/07408170008963874

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

The House of Quality has been widely discussed as a mechanism for converting customer attributes into engineering characteristics to ensure the designqualityof new products and processes. In the past, this process has been subjective and heuristic. In this paper, we present a mathematical programming model for determining the optimal settings for engineering characteristics based on value functions constructedtocapture customer preferences. The model can be used with either traditional subjective measures of customer preference or incorporate empirical models based on quantitative data. The robustness of the optimal solution to randomness in parameter estimates is investigated. An example is used to demonstrate the procedure.

ISSN:0740-817X    

DOI:10.1080/07408170008963875

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

Consider the production of an evolving family of similar products, each having a well-defined life cycle. The fundamental production resources are inherently flexible, i.e., reconfigurable and reprogrammable. Two distinct strategies can be followed in configuring production facilities: (1) focused facilities, where a facility is dedicated to one product at a time, but may be reassigned; and (2) nonfocused facilities, where setup operations permit a variety of products to be produced during a given planning period. When focused facilities are used, which is a common strategy in some electronics companies, products must be assigned to specific facilities. If facilities are not identical, and capacity is limited, then changing production requirements may force reassignment of products from one facility to another. Thus, the product assignment/reassignment decision may have a significant impact on the production capacity required. This paper concentrates on the product assignment/reassignment decision when a pure focused facility strategy is used. This problem is analyzed and a number of insights are developed. Based on this analysis, the problem is reformulated and an optimal solution procedure based on a multi-commodity network flow model is presented and tested for the product assignment/reassignment decision

ISSN:0740-817X    

DOI:10.1080/07408170008963876

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

The loading problem in a Flexible Manufacturing System (FMS) involves allocating operations and associated cutting tools to machines for a given set of parts. There may be different environments for the loading problem that resultfromthree ways of grouping machines in anPMS, i.e., no grouping, partial grouping, and total grouping. Unlike most previous studies on the loading problem for the configurations of no grouping and total grouping, thispaperfocuses on the loading problem resulting from partial grouping, in which each machine is tooled differently but each operation can be processed by one or more machines. Two types of heuristic algorithms are suggested for the loading problem with the objectiveofminimizing the maximum workload of the machines. Performancesofthe suggested loading algorithms are tested on randomly generated test problems and the results show that the suggested algorithms perform better than existing ones. In addition, it is found from simulation experiments that loading plansfrompartial grouping give significantly better performance than those from total grouping.

ISSN:0740-817X    

DOI:10.1080/07408170008963877

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

One of the dilemmas that manufacturers face involves the tradeoff between the cost of maintaining a variety of production processes, and the cost of not having the ideal process for every product that they produce. This issue is continuing to become more of a problem as manufacturers are forced by market conditions to offer a wider selection of products. We study an instance of this problem in the manufacture of sheet metal parts. We model the problemofselecting and/or designing tools to punch holes in these parts. The cost of not having an “ideal process” is the cost of not having a tool that precisely matches a hole'sdesigndiameter. We consider both general “process deviation” costs as well as the Taguchi loss function. Solution procedures are provided for several versions of the problem.

ISSN:0740-817X    

DOI:10.1080/07408170008963878

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

Reverse engineering is the process of developing a Computer Aided Design(CAD)model and a manufacturing database for an existing part. This process is used inCADmodeling of part prototypes, in designing molds, and in automated inspection of parts with complex surfaces. The work reported in this paper is on the automatic segmentation of 3-Dimensional(3-D)digitized data captured by a laser scanner or a Coordinate Measuring Machine (CMM) for reverse engineering applications. Automatic surface segmentation of digitized data is achieved using a combination of region and edge based approaches. It is assumed that the part surface contains planar as well as curved surfaces that are embedded in a base surface. The part surface should be visible to a single scanning probe(21/2D object). Neural network algorithms are developedforsurface segmentation and edge detection. A back propagation network is used to segment part surfaces into surface primitives which are homogenous in their intrinsic differential geometric properties. The method is based on the computation of Gaussian and mean curvatures of the surface. They are obtained by locally approximating the object surface using quadratic polynomials. The Gaussian and mean curvatures are used as input to the neural network which outputs an initial region-based segmentation in the form of a curvature sign map. An edge based segmentation is also performed using the partial derivativesofdepth values. Here, the output of the Laplacian operator and the unit surface normal are computed and used as input to a Self-Organized Mapping (SOM) network. This network is used to findtheedge points on the digitized data. The combination of the region based and the edge based approaches, segment the data into primitive surface regions. The uniqueness of our approach is in automatic calculation of the threshold level for segmentation, and on the adaptability of the method to various noise levels in the digitized data. The developed algorithms and sample results are described in the paper

ISSN:0740-817X    

DOI:10.1080/07408170008963879

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

A fundamental element in operating a competitive manufacturing system is the ability to control material, cost, and other production resources required to transform the raw material to a finished product. To successfully control cost, it is essential that a reliable assessmentofthe tasks required to manufacture the product be made. This involves identifying the operations and the machinetoolsrequired. In this research, a method of decomposing polyhedral components to generate all possible ways to process the part is presented. The technique takes as input the geometric design data of the product, analyzes and interprets the design to identify the volume of material to be machined out from the raw material block to obtain the finished product. The volume of material to be removed are characterized to generate various approach directions from which the material can be machined out. The alternate tool approach directions are used to construct anAND/ORgraph that captures the process alternatives. Using this graphical representation, a model is proposed for selecting the best process plan based on some user defined criterion. The developed procedure can be integrated into aCAD/CAMsystem to provide the required linkage between design and manufacturing and thus, automate a critical link in manufacturing.

ISSN:0740-817X    

DOI:10.1080/07408170008963880

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor

摘要:

This paper is a case study that describes a hybrid system integrating fuzzy logic, neural networks and algorithmic optimizationforuse in the ceramics industry.Aprediction module estimates two quality metrics of slip-cast pieces through the simultaneous executionof twoneural networks. A process improvement algorithm optimizes controllable process settings using the neural network prediction module in the objective function. An expert system module contains a hierarchy of two fuzzy logic rule bases. The rule bases prescribe processing times customized to individual production lines given ambient conditions, mold characteristics and the neural network predictions. This paper demonstrates the applicability of newer computational techniques to a very traditional manufacturing process and the system has been implemented at amajorUS plant.

ISSN:0740-817X    

DOI:10.1080/07408170008963881

出版商:Taylor & Francis Group    

年代:2000

数据来源: Taylor