Manufacturing Cost Function Research Articles

An interactive method for computer-aided optimal process tolerance design based on automated decision making

Interactive and integrated design and manufacturing can be a useful strategy for designers to reach the efficient design through the cognitive or physical interactions. Process tolerance design is a key tool in the integrated design and manufacturing to reach a product with high quality and low cost. Since the optimal tolerance allocation involves several aspects of the design, manufacturing and quality issues, it is always a time consuming and difficult procedure, especially for complex products. Therefore, to overcome these difficulties, a computer-aided approach for optimal tolerance design of manufacturing process is needed in the design stage. In this paper, a novel interactive framework is introduced for computer-aided multi-objective optimal process tolerance design established upon entropy-based decision making. According to the proposed method, the optimal process tolerances of components are allocated through a multi-objective optimization problem where the process capability function and the overall manufacturing cost should be simultaneously optimized. To model the proper objective functions, the new formulations of process capability and manufacturing cost functions are proposed based on the design and customer’s requirements on the virtual model in CAD software, and the experimental observations, respectively. The non-dominated sorting genetic algorithm II is used for solving the multi-criteria optimization. For automated decision making to find the best process tolerances from the optimal Pareto solutions without objective weighting, an improved entropy-based TOPSIS is used. Based on the obtained optimal process tolerances and specifications, the process planning procedure can be carried out. Finally, to illustrate the capability of the proposed method and to validate it, a windmill transmission assembly as a case study is considered and the computational results are compared and discussed.

A closed-form method for statistical tolerance allocation considering quality loss and different kinds of manufacturing cost functions

In order to specify proper tolerances in the product design process, the tolerance optimization model should be established properly and solved accurately. In this paper, several kinds of widely used manufacturing cost functions, including exponential function, reciprocal power function, and polynomial function, are considered simultaneously to calculate the manufacturing cost of different components. Then, the most suitable manufacturing cost function for each component is chosen so that the fitting error is minimized. After the manufacturing cost functions are determined, the tolerance optimization model is established to minimize the total cost including manufacturing cost and quality loss. In the tolerance optimization model, both assembly tolerance constraint and process accuracy constraints are considered. In order to solve the tolerance optimization model accurately, the Lagrange multiplier method is applied and closed-form solutions of optimal tolerances are established. The calculating results demonstrate that the proposed method has high accuracy.

Improvement in quality and productivity of an assembled product: A riskless approach

In this paper, to show the importance of improvement on savings of costs in a riskless sense, the quality loss and manufacturing cost functions are employed to allocate the components tolerances of an assembled product simultaneous with taking appropriate improvement operations. The use of improvement operations reduces the variability of the process while increasing the production costs. To apply improvement operations in a riskless sense, which actually does not impose additional costs to the producers, we take advantages of the trade-off between improvement costs and tolerance costs. Therefore, a series of algorithms are proposed for simultaneous selection of tolerances and improvement operations so as to minimize the total cost. The use of our approach helps considerably save large amounts of computer time by pruning many unnecessary evaluations. It is shown that proper choices of both improvement operations and tolerances have an important impact to enhance productivity and quality.

Development of a function oriented computer aided tolerancing (FOCAT) system

Functional tolerancing of a mechanical part depends on the assembly and manufacturing function. This paper presents an approach for functional tolerance design and optimization. Functional surfaces are classified according to ISO specification. Dimensional and geometric tolerance types are specified based on design rules. Well-constrained analysis is presented to avoid over- and under- constrained tolerance design. A tolerance values optimization model is established with manufacturing cost functions and assembly stackup constraints. A computer-aided tolerancing (CAT) system is developed to provide designer with an effective tool for ensuring the functional tolerancing of the entire assembly. The system is applied to perform a tolerance design for a three-dimensional (3D) assembly .

Concurrent design of a geometric parameter and tolerance for assembly and cost

Geometric parameter and tolerance design are two important phases in product design and they will affect the assembly functionality and manufacturing cost of a product. The aim is to present a new method of parameter and tolerance design for concurrent engineering. In the nominal domain, a graphical representation of the linkage of geometric constraints is termed the nominal loop circuit, which helps to formulate the stack path of parameters into parameter equations. In the variational domain, the nominal loop circuit is extended as the variational loop circuit, which helps to established assembly stack-up functions. In the tolerance domain, tolerance types are designed and tolerance inequations formulated. Based on the empirical parameter and tolerance versus manufacturing cost data, manufacturing cost functions are established. Based on the assembly and cost functions, parameter equations and tolerances inequations, the mathematical model of parameter and tolerance design is established and a genetic algorithm is used to find multi-objective optimum solutions of parameters and tolerances. The method not only can design concurrently parameter and tolerance for assembly and cost, but also synthetically consider dimensional and geometric tolerances. Applications of the proposed method have been illustrated.

Managing multiple dimensions of manufacturing performance — an exploratory study

Drawing on qualitative data collected during semi-structured interviews with 36 profit centre managers in manufacturing firms in Victoria, Australia, this study seeks to explore the mechanisms used to manage multiple manufacturing performance dimensions arising from the pursuit of profit centre strategy. Where measures capture potentially conflicting influences on the manufacturing cost function, strategy implementation is facilitated by loosening control reactions to cost variances and through explicit attempts to integrate multiple measures. However, a joint emphasis on performance dimensions relating to manufacturing efficiency and customer responsiveness emerges as problematic. In contrast, a joint emphasis on quality and efficiency is relatively easily managed. It is suggested that in the context of responsiveness strategies, the difficulty of designing complete measures inhibits the effectiveness of performance measurement systems as a facilitator of strategy implementation.

Manufacturing feature recognition toward integration with process planning

Process planning plays a key role by linking CAD and CAM. Its front-end is feature recognition, but feature recognition research has not been in accord with the requirements of process planning. This paper presents an effort for integrating the two activities: feature-based machining sequence generation primarily based on tool capabilities. The system recognizes only manufacturable features by consulting the tool database, and simultaneously constructs dependencies among the features. Then, the A* algorithm is used to search for an optimal machining sequence by the aid of the feature dependencies and a manufacturing cost function.

A STUDY OF OPTIMAL DESIGN UNDER CONFLICT USING MODELS OF MULTI-PLAYER GAMES

In the broad context of modelling for system design, it is normally assumed that all decision-makers cooperate fully and thus avoid conflict. However, this is not always possible, in which case the design process is best modelled and studied as a multi-player game. The objective in this paper is to present and illustrate such a general game-theoretic framework for design modelling. In particular, explicit solutions are computed and interpreted for conservative or minmax, Pareto, Nash and Stackelberg games in a simple pressure vessel design example in which two players interact strategically, one of whom wants to minimize the weight and other wishes to maximize the volume. In another example in which a rotating disk is to be optimized for two objectives related to its design and manufacture, the Pareto solutions show how a novel manufacturing cost function can improve, under assumptions of a cooperative game, the optimal shape that was obtained under a single objective formulation related to design alone.

Estimating the distributions of manufactured dimensions with the beta probability density function

As mentioned by the author [Ph.D. Dissertation, University of New South Wales, 1989] the percentage of scrap and rework in the manufacturing cost function has been shown to be a function of the shape and variability of the distribution of the manufactured dimensions and of the allocated manufactured tolerances. Therefore questions pertaining to the choice of specific distributions and the determination of the parameters are of interest. This paper presents a method of statistical data analysis to represent the distribution of manufactured dimensions from observational data with a beta probability density function. Instead of using the four moments, a simpler method has been developed which estimates the two bounds first, then estimates the shape exponents using the first and second moments and these four parameters can be improved continuously until some predetermined accuracy is obtained. The use of the distributions of dimensions produced by manufacturing processes is to estimate process capabilities and the probabilities of selected tolerances being achieved by a process or a given set of manufacturing conditions.

Regional Energy Substitution: Results from a Dynamic Input Demand Model

In this note we report results of a study of energy substitution in manufacturing, using twodigit data disaggregated by region in a dynamic, disequilibrium model of firm input demand. The question of regional differences in the impacts of energy price changes is an important one. National energy policy is worked out in a climate of great conflict among regions, based on real or imagined differences in the perceptions of the role of energy in production. For example, it has become commonplace to hear that the older regions, such as the Northeast, will be hurt more by energy price increases than newer regions, such as the Southwest. In a previous paper we presented results of estimating regional models with a static, full equilibrium manufacturing cost function [6]. We used pre-1974 data, which may have reflected something close to long-run equilibrium positions for firms. It seems valuable, however, to analyze data from a slightly later period with one of the more recently developed models that permit firms to be out of long-run equilibrium. This could yield substantially greater understanding of the direction and speed of induced input adjustments undertaken by firms of the different regions in response to the large price changes of the 1970s.