Comparative study of tolerance on cost for various metal-removal processes

Tolerance design has been identified as one of the key areas to realize the objective of producing quality goods at affordable cost. The impact of tolerance on the cost of manufacture for various metal-removal processes are shown by cost models. These cost models are in turn used in tolerance design to arrive at the relative cost of manufacture to various tolerances. Most of the cost models available untill recently were based on data from industries in the USA. However, Gunasekaran et al. (Gunasekaran, K., Neelakrishnan, S., Ragu, K. and Mohanram, P.V., Influence of tolerance on cost for various manufacturing processes, in National Conference on CAGQ — 2004, Thiagarajar College of Engineering, Madurai, India, 2004) presented the relative cost of tightening manufacture in Indian industries for attaining various tolerance values in Indian rupees and the results have been presented in graphical format. These formats are useful in determining the cost involved when tolerance synthesis methods are used to allocate tolerances to parts. In order to have an understanding of the costs involved to manufacture to a specific tolerance among the job shop-type and organized sector found in Indian industry, the cost versus tolerance data presented by Gunasekaran et al. (job-shop industry) have been compared with further data gathered by the present authors. In addition, the comparison includes the cost curves presented by Chase et al. (Chase, K.W., Greenwood, W.H., Loosli, B.G. and Hauglund, L.F., Least cost tolerance allocation for mechanical assemblies with automated process selection, J. Manuf. Rev. ASME, 1989, 2(4), 49–59). This is especially useful in analysing the differences in sourcing from a job shop versus the organized sector. In addition, the results that are displayed graphically are also compared with the cost models that already exist. In addition, one of the benefits of the cost curves is illustrated with a case study of a simple component.     

制造质量记录信息管理系统的总体设计与开发

本文首先论述了质量记录在计算机辅助质量管理（ＣＡＱＭＳ）中的作用及地位，随后阐述制造质量记录信息管理系统的总体设计方案，以上工作在计算机集成制造系统（ＣＩＭＳ）应用中将得到体现。     

Sequential optimization of parameter and tolerance design for multiple dynamic quality characteristics

System design, parameter design and tolerance design are the three stages of design process as presented by G. Taguchi. Systems design identifies the basic elements of the design to provide new or improved products to customers. Parameter design determines the optimal parameter settings, which will minimize variation from the target performance of the product. Tolerance design finally identifies the components of the design, which are sensitive in terms of affecting the quality of the product, and establishes tolerance limits that will give the required level of variation in the design. Most studies have focused primarily on optimizing the parameter design or tolerance design for multiple static quality characteristics. In this paper, a mathematical formula corresponding to the model is derived from Taguchi's quadratic quality loss function to minimize the expected total cost for the parameter design of multiple dynamic quality characteristics. When the optimal parameter design is not sufficient to reduce the output variation, the first-order Taylor series expansion is then used to analyse the variations of noise factors for optimizing the tolerance design. It concludes with an example demonstrating this approach.     

A comparison of deterministic and statistical sampling techniques for quality analysis of integrated circuits

There has been a great amount of publicity about Taguchi methods which employ deterministic sampling techniques for robust design. Also given wide exposition in the literature is tolerance design which achieves similar objectives but employs random sampling techniques. The question arises as to which approach—random or deterministic—is more suitable for robust design of integrated circuits. Robust design is a two-step process and quality analysis—the first step—involves the estimation of ‘quality factors’, which measure the effect of noise on the quality of system performance. This paper concentrates on the quality analysis of integrated circuits. A comparison is made between the deterministic sampling technique based on Taguchi's orthogonal arrays and the random sampling technique based on the Monte Carlo method, the objective being to determine which of the two gives more reliable (i.e. more consistent) estimates of quality factors. Results obtained indicated that the Monte Carlo method gave estimates of quality which were at least 40 per cent more consistent than orthogonal arrays. The accuracy of prediction of quality by Taguchi's orthogonal arrays is strongly affected by the choice of parameter quantization levels—a disadvantage—since there is a very large number (theoretically infinite) of choices of quantization levels for each parameter of an integrated circuit. The cost of the Monte Carlo method is independent of the dimensionality (number of designable parameters), being governed only by the confidence levels required for quality factors, whereas the size of orthogonal array required for a given problem is partly dependent on the number of circuit parameters. Two integrated circuits—a 7-parameter CMOS voltage reference and a 20-parameter bipolar operational amplifier—were employed in the investigation. Quality factors of interest included performance variability, acceptability (relative to customer specifications) and deviation from target.     

Parameter tolerance design for electrical circuits

Realistic circuit design requires that unavoidable tolerances on component parameters be taken into account, particularly in situations where a circuit is to be mass-produced. Since specifications are normally imposed on circuit performance, parameter tolerances can have the undesirable effect of reducing manufacturing yield (i.e. the percentage of circuits which meet specifications) to values below unity, thereby effectively increasing circuit cost. Approaches have been developed to electrical circuit design which incorporate aspects of parameter tolerance variations at the various stages of design, thus enabling tolerance effects to be assessed and minimized. There are two principal approaches: statistical and deterministic. The first uses probabilistic techniques to predict variations in circuit performance, whereas the second uses deterministic (i.e. non-stochastic) methods. Within each group, three types of problems are important: first, the maximization of yield, secondly, the minimization of circuit unit cost and, thirdly, the minimization of performance variability. This paper discusses some important advances in the statistical approach to tolerance design. Monte Carlo analysis is almost invariably an important component of the procedure: random fluctuations in parameter values are simulated according to some probability density function and inserted into a computer circuit simulation program which computes corresponding circuit performance variations. The procedure — also referred to as tolerance analysis — not only allows the designer to predict expected performance fluctuations but also presents him with information regarding the relative location of acceptable and non-acceptable circuits in component parameter space. The Monte Carlo method can handle without difficult any number of component parameters and performance functions; moreover, statistical dependence among parameters is readily handled. The algorithm presented here is experimentally validated through successful design of practical circuits and is applicable to both discrete and integrated circuits. Strategies which ensure computational efficiency of the methods are discussed and a cost/benefit analysis carried out for a typical circuit.     

Integrated quality and quantity modeling of a production line

During the past three decades, the success of the Toyota Production System has spurred much research in manufacturing systems engineering. Productivity and quality have been extensively studied, but there is little research in their intersection. The goal of this paper is to analyze how production system design, quality, and productivity are inter-related in small production systems. We develop a new Markov process model for machines with both quality and operational failures, and we identify important differences between types of quality failures. We also develop models for two-machine systems, with infinite buffers, buffers of size zero, and finite buffers. We calculate total production rate, effective production rate (ie, the production rate of good parts), and yield. Numerical studies using these models show that when the first machine has quality failures and the inspection occurs only at the second machine, there are cases in which the effective production rate increases as buffer sizes increase, and there are cases in which the effective production rate decreases for larger buffers. We propose extensions to larger systems. Correspondence to: Stanley B. GershwinWe are grateful for support from the Singapore-MIT Alliance, the General Motors Research and Development Center, and PSA Peugeot-Citroën.     

Design for manufacturing: use of a spreadsheet model of manufacturability to optimize product design and development

Product design typically precedes factory implementation and requires an understanding of factory logistics to achieve optimized design for manufacturing. We developed a spreadsheet-based model of a future factory at the very earliest stages of design of an advanced range of medical products. The algorithms have since been applied to a wide range of product designs and manufacturing operations. The model was used to optimize product design for manufacturability, develop cost-effective manufacturing processes, and design and optimize the new factory. The model incorporates cost, inventory, and factory responsiveness, and can be applied to find the optimum solution between cost and cycle time reduction. Design changes initiated as a result of analysis using the model reduced subsequent manufacturing costs significantly and reduced the launch program by two years, because confidence in the model justified the commissioning of full-scale manufacturing equipment when the product was still only at the concept stage. Electronic Publication     

Concurrent optimization of assembly tolerances for quality with position control using scatter search approach

Tolerance allocation to individual parts in any assembly should be a vital design function with which both the design and manufacturing engineers are concerned. Generally design engineers prefer to have tighter tolerances to ensure the quality of their design, whereas manufacturing engineers prefer loose tolerances for ease of production and the need to be economical. This paper introduces a concurrent tolerance approach, which determines optimal product tolerances and minimizes combined manufacturing and quality related costs in the early stages of design. A non-linear multivariable optimization model is formulated here for assembly. A combinatorial optimization problem by treating cost minimization as the objective function and stack-up conditions as the constraints are solved using scatter search algorithm. In order to further explore the influence of geometric tolerances in quality as well as in the manufacturing cost, position control is included in the model. The results show how position control enhances quality and reduces cost.     

A multi-plant tolerance allocation model for products manufactured in a multi-plant collaborative manufacturing environment

To produce an assembled product, the components need to be manufactured within the allocated tolerances such that the assembly operations can be performed to produce the final product. In a collaborative manufacturing environment, the components of a product may be manufactured at different plants distributed at various locations. There are different manufacturing operations with various process capabilities at the multiple plants. If the components are distributed to the manufacturing operations at the different plants, the working tolerances of the components may be allocated differently. In this research, a multi-plant tolerance allocation model is presented. At the first stage, given the blueprint dimensions and tolerances of a designed product, a cross-plant tolerance allocation is performed to determine the working tolerance of each of the components by considering all the feasible manufacturing operations of the available plants. The primary objective at the first stage is to maximize the cumulative sum of working tolerances. At the second stage, the components are assigned to the suitable plants to perform the required manufacturing operations. A mathematical programming model is presented to distribute the components to the suitable plants to achieve the objective of minimizing multi-plant manufacturing costs. As a result, the working tolerances can be allocated for the components with suitable manufacturing operations to achieve the tolerance objective. In addition, the manufacturing operations for the components can be performed at the suitable plants with optimized multi-plant manufacturing cost objectives. An example product is demonstrated and discussed.     

Economic tolerance design for quality

This paper provides a few general mathematical models for determining product tolerances which minimize the combined manufacturing costs and quality loss. The models contain quality cost with a quadratic loss function and represent manufacturing costs with geometrical decay functions. The models are also formulated with multiple variables which represent the set of characteristics in a part. Applications of these models include minimizing the total cost with effective tolerance allocation in product design.     

设计与制造中的统计几何公差建模及应用

几何与尺寸公差(形位公差GD&T)广泛用于机械工程设计与制造中重要几何特征的偏差控制.相对较成熟和简单的尺度公差建模与分析,几何公差统计建模与分析更具挑战性,是当前CAD技术中尚未但亟待解决的课题之一.现提出采用统计几何模态模型(SMA)方法解决这一问题.SMA可识别刻划与解释测量数据中的几何特征信号模式及其变化,从而服务于制造中的(公差)质量检验、诊断及变化模式的统计建模.在设计中SMA可进行模态重组综合,从而再现或仿真几何特征偏差的随机变化进行统计几何公差分析.     

A review of synthesis methods for additive manufacturing

With the design freedoms afforded by additive manufacturing (AM) processes, an increasing interest in shape synthesis methods has led to a variety of advances in topology optimisation methods and associated synthesis technologies. In this paper, we identify research issues related to the application of AM to shape synthesis methods, review recent advances in topology optimisation, and outline a vision for future synthesis capabilities.     

Joint optimization in process target and tolerance limit for L -type quality characteristics

Most models reported in the current process target literature assume a nominal-the-best type quality characteristic in determining the optimal process mean value. In real-world industrial settings, however, a number of quality characteristics of interest are of a larger-the-better type (L-type), and the problem of jointly determining the optimum process mean and tolerance limit for the L-type quality characteristic may be of significant practical importance, yet this has largely been overlooked in the literature. In this paper, cost-effective optimization models are developed, and the methods of finding optimum solutions are presented. Numerical examples and sensitivity analysis are given.     

Simultaneous tolerancing for design and manufacturing

This paper presents a new tolerance design theory—simultaneous tolerancing— which works in the concurrent engineering context. After stating the need to develop a simultaneous tolerancing theory by showing the shortcomings of conventional tolerancing technique, the concept of simultaneous tolerancing is given, and its elements are briefly presented. Then we focus our attention on the development of a general mathematical model of optimal tolerancing supporting concurrent engineering. Two commonly used models, worst-case and statistical, are discussed in detail. Next, a method of ‘interim tolerances’, which help to determine an appropriate machining process without using functional tolerances, is proposed. The simultaneous tolerancing theory presented in this paper permits of determining directly optimal machining tolerances in product design, reducing the manufacturing cost and improving the quality of products. Finally, an example is given, showing that the proposed theory is feasible in practice.     

A generic tool for cost estimating in aircraft design

A methodology to estimate the cost implications of design decisions by integrating cost as a design parameter at an early design stage is presented. The model is developed on a hierarchical basis, the manufacturing cost of aircraft fuselage panels being analysed in this paper. The manufacturing cost modelling is original and relies on a genetic-causal method where the drivers of each element of cost are identified relative to the process capability. The cost model is then extended to life cycle costing by computing the Direct Operating Cost as a function of acquisition cost and fuel burn, and coupled with a semi-empirical numerical analysis using Engineering Sciences Data Unit reference data to model the structural integrity of the fuselage shell with regard to material failure and various modes of buckling. The main finding of the paper is that the traditional minimum weight condition is a dated and sub-optimal approach to airframe structural design.     

Construction of closed-form equations and graphical representation for optimal tolerance allocation

The Lagrange multiplier method (LM) is currently used to allocate tolerance for optimum manufacturing cost. This is a tedious iterative process and sometimes it allocates a component's tolerance outside its process tolerance limits. The present work develops a graphical representation which can help the process engineer to visualize the minimum and maximum values for assembly tolerances. The graphical representation developed can also help the process engineer to determine the exact total manufacturing cost of the assembly and help to fix the tolerance, which would not fall outside the limits prescribed. A simple C program is developed to construct the closed-form equations (CFE), and a single EXCEL graphical representation is derived for assembly tolerance, allocated tolerance, and total manufacturing cost. The developed algorithm has been demonstrated on a two- to five-component linear assembly, to help the process/manufacturing engineer's visualization before determining the tolerance specification on component dimensions. The test results show a maximum percentage deviation of 0.09% of assembly tolerance and 0.33% of total manufacturing cost between the LM and the newly developed CFE method.     

A manufacturing network design model based on processor and worker capabilities

This paper presents an optimization methodology to design networks of manufacturing facilities producing several products under deterministic demand. The bill of materials and the operations for each product are taken into account through the use of a product-state graph. Starting from the current state of the manufacturing network, the approach considers a multi-period planning horizon. For each period it specifies the facilities to open within the set of current and potential facilities, the mission for each of the centres in the selected facilities, the equipment to be used for producing the goods, and the structure of the network. Taking human resource competencies into account, the approach selects the type of workers to use for executing the manufacturing tasks. The transfer of resources between plants is also considered. A multi-period mixed integer linear programming model is formulated, a solution method based on the addition of specialized cuts is proposed and computational results are presented.     

A hybrid GA/heuristic approach to the simultaneous scheduling of machines and automated guided vehicles

In this paper, the problem of simultaneous scheduling of machines and identical automated guided vehicles (AGVs) in flexible manufacturing systems is addressed with the objective of minimizing the makespan. This problem is composed of two interrelated decision problems: the scheduling of machines, and the scheduling of AGVs. Both problems are known to be NP-complete, resulting in a more complicated NP-complete problem when they are considered simultaneously. A new hybrid Genetic-algorithm/heuristic coding scheme is developed for the studied problem. The developed coding scheme is combined with a set of genetic algorithm (GA) operators selected from the literature of the applications of GAs to the scheduling problems. The algorithm is applied to a set of 82 test problems, which was constructed by other researchers, and the comparison of the results indicates the superior performance of the developed coding.     

Performance measurement for a manufacturing system based on quality,cost and time

Product quality, manufacturing cost and manufacturing time are three of the major concerns in a manufacturing system. This study proposes a product capability index to evaluate the quality of a multi-process product and addresses the relationship between process yield and the product capability index. In addition, this paper develops a time–cost index to assess manufacturing cost and manufacturing time. The quality index and time–cost index are simultaneously used to monitor product quality and manufacturing time on a quality and time–cost analysis chart. The quality and time–cost analysis chart, providing accurate information on the quality status and time–cost status for each process, helps to initiate, effectively and efficiently, quality improvement plans to elevate product quality and manufacturing time and manufacturing cost control for a manufacturing system.     

A genetic algorithm for manufacturing cell formation with multiple routes and multiple objectives

This paper presents a genetic algorithm (GA) approach to the machine-component grouping problem with multiple objectives: minimizing costs due to intercell and intracell part movements; minimizing the total within cell load variation; and minimizing exceptional elements. Manufacturing cells are formed based on production data, e.g. part routing sequence, production volume and workload. Also, we will discuss the implication of part alternative routings and the method we suggest to deal with it. Special genetic operators are developed and multiple experiments are performed. Finally, the results obtained with the proposed algorithm on the tested problems are compared with those of others.