Optimal concurrent product design and process planning based on the requirements of individual customers in one-of-a-kind production

One-of-a-kind production is a new manufacturing paradigm for producing customised products based on the requirements of individual customers while maintaining the quality and efficiency of mass production. This research addresses the issues in optimal concurrent product design and process planning based on the requirements of individual customers. In this work, a hybrid AND-OR graph is developed to model the variations of design configurations/parameters and manufacturing processes/parameters in a generic product family. Since different design configurations and parameters can be created from the same customer requirements, and each design can be further achieved through alternative manufacturing processes and parameters, co-evolutionary genetic programming and numerical optimisation are employed to identify the optimal product design configuration/parameters and manufacturing process/parameters. A case study is introduced to identify the optimal design configuration/parameters and manufacturing process/parameters of custom window products of an industrial company to demonstrate the effectiveness of the developed method.     

A new tolerance design method for a secondary rechargeable battery using design of experiments with mixture

Mixing errors in the manufacturing process of a mixture may cause a sizeable variation in the performance of the product, leading to the need for the tolerance design. Even though a variety of procedures have been proposed for the optimal tolerance design based on quality loss and manufacturing costs, there are no available tolerance design methods when mixing errors exist in the manufacturing process of a mixture. In this article, we propose a new tolerance design method for the case where mixing errors are involved in massive manufacturing process of a secondary rechargeable battery. Using an approximation method, we derive quality loss function, reflecting the effects of mixing errors on the product performances. Statistical design of mixture experiments is applied to build empirical models of performances as functions of component proportions in the corresponding quality loss function. A real‐life case study on the tolerance design of a secondary battery is provided for the illustration of the proposed method. The results show the efficiency of the proposed method in designing the tolerances to minimize the quality loss and manufacturing costs. Copyright © 2008 John Wiley & Sons, Ltd.     

An Economic Approach to the Management of High‐Quality Processes

Modern manufacturing developments have forced researchers to investigate alternative quality control techniques for high‐quality processes. The cumulative count of conforming (CCC) control chart is a powerful alternative approach for monitoring high‐quality processes for which traditional control charts are inadequate. This study develops a mathematical model for the economic design of the CCC control chart and presents an application of the proposed model. On the basis of the results of the application, the economic and classical CCC control chart designs of the CCC control chart are compared. The optimal design parameters for different defective fractions are tabulated, and a sensitivity analysis of the model is presented for the CCC control chart user to determine the optimal economic design parameters and minimum hourly costs for one production run according to different defective fractions, cost, time, and process parameters. Copyright © 2012 John Wiley & Sons, Ltd.     

Combined parameter and tolerance design optimization with quality and cost

The need to remain competitive for survival in the current world market has led manufacturing sectors to consider the low cost and high quality of product and process design. Production of quality products at low cost in today's manufacturing industry requires simultaneous consideration of product design and process planning, particularly in the early stage of design and planning. During product design, parameter design determines the design target (design setting) and tolerance design determines design tolerance. During process design, the parameter design determines the process mean (process setting) and tolerance design determines process tolerance. This study provides a mathematical relationship to link the elements of design target, design tolerance, process mean and process tolerance in one equation. By following this equation, manufacturability for all possible combinations of product and process design can be ensured, which increases the flexibility of both product design and process planning. With this in mind, an analysis model that includes manufacturing cost and quality loss simultaneously has been developed to determine the optimal values of design tolerance, process mean and process tolerance. The proposed model provides a method of combining the optimization of parameter and tolerance design over product/process in the early stage of design.     

INTEGRATING PRODUCT DESIGN AND MANUFACTURING: A GAME THEORETIC APPROACH

One approach for increasing the quality of a product and the efficiency of its realization is to pay attention to the integration of product design and manufacturing. An integrated product realization process must be able to accommodate sequential stages of activity along a product realization time-line, independent information flow between stages, and trade-offs between various activities and factors. In this paper, a decision-based approach that is consistent with such characteristics is explored. This approach is anchored in game theory and a decision construct, namely, the Compromise Decision Support Problem. The merging of these two elements provides a mathematical and systematic basis for coordinating product design and manufacturing. This approach is illustrated via an example, namely, the redesign of a common component platform for a family of absorber-evaporator modules for absorption refrigeration, in order to reduce their costs and production times. The focus is on the method rather than the results per se.     

Coordinated optimisation of platform-driven product line planning by bilevel programming

Product line planning (PLP) aims at an optimal combination of product feature offerings, suggesting itself to be a determinant decision for a company to satisfy diverse customer needs and gain competitive advantages. Fulfilment of planned product lines must make trade-offs between product variety and production costs. To balance the costs of product lines, manufacturers often adopt a product platform configuration (PPC) approach to redesign product and process platforms by adding new modules to the legacy platforms. The PPC is an effective means of providing product variety while controlling the manufacturing costs. The PLP and PPC problems have traditionally been investigated separately in the marketing research and engineering design fields. It is important to coordinate PLP and PPC decisions within a coherent optimisation framework. This paper proposes a bilevel mixed 0–1 nonlinear programming model to formulate coordinated optimisation for platform-driven product line planning. The upper level deals with the PLP problem by maximising the profit of an entire product line, whilst the lower level copes with the multiple product platforms optimisation for the optimal PPC in accordance with the upper level decisions of product line structure. To solve this bilevel programming model, a bilevel genetic algorithm is developed to find the optimal solution. A case study of coordinated optimisation between an automobile line and its product platforms is presented to demonstrate the feasibility and effectiveness of the proposed bilevel programming in comparison with a typical ‘all-in-one’ approach and a non-joint optimisation programming.     

A Novel Approach to Simultaneous Robust Design of Product Parameters and Tolerances Using Quality Loss and Multivariate ANOVA Concepts

Design and development of high quality products are of utmost importance to any production plant. Product design consists of parameter design and tolerance design, which affect the product performances and the manufacturing costs, respectively. Most products involve more than one quality feature. Design and development of such products raise multi‐response surface problems in which it is necessary to determine the optimal values of parameters and the tolerances for all responses simultaneously. In this research, an approach for simultaneous robust parameter and tolerance design is proposed to deal with multi‐response problems. The proposed method employs quality loss concept and one‐way multivariate analysis of variance. Two simulation studies are performed to validate the applicability of the proposed method. Research findings show that the proposed method performs better in quality improvement as well as in cost reduction than the existing methods. The variances of the responses are also lower than those of the other methods, that is, the proposed method results in a more robust approach to product design. Copyright © 2016 John Wiley & Sons, Ltd.     

Tolerance chart balancing for machining process planning

This paper provides a mathematical model for tolerance chart balancing for machining process planning. The formulation of the proposed model is based on the graphic ‘rooted tree’ representation technique in describing the sequence of the machining process. The criteria considered in the presented study are based on the combined effects of manufacturing cost and quality loss under constraints such as process capability limits, design functionality restrictions, and product quality requirements. Applications of these models include minimizing the total cost of manufacturing activities and quality related issues with process selection and tolerance allocation in machining process planning, particularly in the early stage of planning.     

Joint production control and product quality decision making in a failure prone multiple-product manufacturing system

This paper considers joint production control and product quality specifications decision making in unreliable multiple-product manufacturing system. This is with the knowledge that an optimum compromise should guide the decision making process. In fact, tight process specifications will generally lead to products with good quality and higher market values, but at the same time associated with a higher rate of non-conforming parts rejection leading to higher non quality costs and lower plant productivity. Moreover, in unreliable manufacturing context the decision maker should adopt an adequate production policy to hedge against future capacity shortages caused by machine failures in order to meet customer demand. This paper intends to extend previous findings to tackle this problem and study the overall decision making process aiming to guide the production and quality specification decisions in multiple-product context. The overall optimal decision policy is defined here as one that maximises the long term average per unit time profit of a combined measure of quality and quantity dependent sales revenue, minus inventory and backlog costs, in the presence of random plant failures and random repair durations.     

Economic design of X̄ and R charts under Weibull shock models

This paper considers the problem of a continuous production process where both the mean and variance are simultaneously monitored by an X̄ and R chart respectively, and generalizes the model of Costa (IIE Transactions 1993; 25 (6):27–33). The product variable quality characteristic is assumed to be normally distributed and the process is subject to two independent assignable causes (such as tool wear‐out, overheating or vibration). One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. It is also assumed that the occurrence times of the assignable causes are described by Weibull distributions with increasing failure rates. A cost model is developed and a non‐uniform sampling interval scheme is adopted. A two‐step search procedure is employed to determine the optimal design parameters. The relative contribution of the paper over the results obtained by Costa is addressed. A sensitivity analysis of the model is conducted and the cost savings associated with the use of non‐uniform sampling intervals instead of constant sampling intervals are evaluated. The economic design model is then extended to an economic–statistical design model for achieving desired levels of statistical performance while minimizing the expected cost. Performances of purely economic design and economic–statistical design are compared. Copyright © 2000 John Wiley & Sons, Ltd.     

An Economic Analysis for Product and Process Design

Industry competitiveness requires the best possible quality-price combination; therefore, cost analysis is usually required at the design stages. Off-line quality control methods are conducted at the product and process design stages to improve manufacturing costs and quality of the product. An economic analysis is proposed in this article that can be carried out along with the known parameter design methods. The economic analysis in the experimental design does not add experimental costs and shows potential savings. The model minimizes the total expected quality cost, which includes the cost of using a set of factor levels and its expected quality loss.     

本体范畴下一种新的功能定义及对应的产品设计过程划分

产品设计过程是产品生命周期中的一个重要环节,决定了后续制造阶段的成本和最终产品的质量.产品设计过程的本质就是对设计问题进行求解的过程,是在不确定的状态下所进行的实现自己或客观主体目的的一个决策过程,而功能就是决定产品设计过程本质的一个重要内容.为此,以功能为核心,首先对以往功能的相关研究进行综述.分析了功能研究的现状,...     

Design sensitivity analysis and optimization for minimizing springback of sheet‐formed part

The springback is a manufacturing defect in the stamping process and causes difficulty in product assembly. An impediment to the use of lighter‐weight, higher‐strength materials in manufacturing is relative lack of understanding about how these materials respond to complex forming processes. The springback can be reduced by using an optimized combination of die, punch, and blank holder shapes together with friction and blank‐holding force. An optimized process can be determined using a gradient‐based optimization to minimize the springback. For an effective optimization of the stamping process, development of an efficient design sensitivity analysis (DSA) for the springback with respect to these process parameters is crucial. A continuum‐based shape and configuration DSA method for the stamping process has been developed using a non‐linear shell model. The material derivative is used to develop the continuum‐based design sensitivity. The design sensitivity equation is solved without iteration at each converged load step in the finite deformation elastoplastic non‐linear analysis with frictional contact, which makes sensitivity calculation very efficient. Numerical implementation of the proposed shape and configuration DSA method is performed using the meshfree method. The accuracy and efficiency of the proposed method are illustrated by minimizing the springback in a benchmark S‐rail problem. Copyright © 2007 John Wiley & Sons, Ltd.     

The development of a robust design methodology for time‐oriented dynamic quality characteristics with a target profile

Innovative engineering techniques are often sought within the manufacturing environment to improve product quality and promote more cost‐effective strategies. Robust design methods are frequently used to serve this purpose, with the objective of minimizing the variability inherent within a particular process or system. A review of the literature suggests that most robust design research involves the study of static quality characteristics, given a pre‐defined specification interval or region and target value. In addition to proposing a methodology for working with dynamic quality characteristics where the specifications and target value may change over time, this paper offers two other distinct contributions. First, those researchers who have examined dynamic systems traditionally consider the effects of a signal factor on a response variable on the identification of optimal factor settings. In contrast, this paper will consider the effects of a quality characteristic changing over time, thus removing the need to confine the problem to signal–response systems. Furthermore, most researchers consider the optimization of the process mean according to the costs of non‐conforming to an established specification interval or region. This paper, however, utilizes a methodology involving the simultaneous optimization of the process mean and variance while expanding the problem to consider a loss in quality attributed to deviation from a target value over time. Copyright © 2010 John Wiley & Sons, Ltd.     

Optimal tolerance design for product life cycle

This paper provides mathematical models to determine optimal tolerances for which the combined manufacturing costs, quality loss, and scrap/rework costs are minimized. The models include cases such as a single component, as well as multiple components for a product. The models also consider the constraints such as design functionality restrictions, product quality requirements, and process capability limits. The models are mainly developed for application in both engineering management and engineering design.     

基于优化的产品平台参数规划方法

 为满足客户化和全球竞争的需求,企业要实现大规模定制(mass customization,MC).基于公共产品平台的产品族设计是实现大规模定制的一种有效方式,而平台规划是面向产品族设计方法学的核心内容,也是目前研究中的一个热点问题.基于模型参数的平台设计是其方法之一.针对基于一系列标准可变参数的产品平台,用优化方法对产品平台参数进行规划,以满足各种客户需求.该规划方法无需事先人为指定,而是在满足客户需求的前提下,尽可能提高产品族中设计变量的共性,从而确定最好的产品平台的公共参数及其最优值,以及个性参数及其变化值,并以带式输送机为例验证了该方法.     

The impact of the cost of quality on serial supply‐chain network design

This paper presents a model for supply‐chain design that considers the Cost of Quality as well as the traditional manufacturing and distribution costs (SC‐COQ model). It includes three main contributions: (1) the SC‐COQ model internally computes quality costs for the whole supply chain considering the interdependencies among business entities, whereas previous works have assumed exogenously given Cost of Quality functions; (2) the SC‐COQ model can be used at a strategic planning level to design a logistic route that achieves a maximum profit while considering the overall quality level within a supply chain; and (3) we provide two solution methods based on simulated annealing and a genetic algorithm and perform computational experiments on test instances.     

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.     

Quality design of tolerance allocation for sheet metal assembly with resistance spot weld

Tolerance directly influences the functionality of the products and the related manufacturing costs, and tolerance allocation is of great importance for improving the assembly quality. However, the information required to allocate tolerances for complex 3D assemblies is generally not available at the initial design stage. In this paper, a new quality design methodology is developed, which makes use of both original design data obtained by the response surface methodology and the extra interpolation data obtained by the Kriging method. The finite element modelling is presented for the sheet metal assembly process as no explicit relationship of the variations for key characteristic points are available. The robust tolerances can be allocated based on the quality design model. A case study with the typical assembly process of the rear compartment pan and the wheelhouse is carried out in the paper, the tolerance allocation results show that the developed quality design methodology is capable of determining the robust manufacturing tolerance before assembly, which satisfies the product requirements. This method enables a robust tolerancing scheme to be used in the sheet metal assembly process.