Optimal reliability, warranty and price for new products

The success of a new product depends on both engineering decisions (product reliability) and marketing decisions (price, warranty). A higher reliability results in a higher manufacturing cost and higher sale price. Consumers are willing to pay a higher price only if they can be assured about product reliability. Product warranty is one such tool to signal reliability with a longer warranty period indicating better reliability. Better warranty terms result in increased sales and also higher expected warranty servicing costs. Warranty costs are reduced by improvements in product reliability. Learning effects result in the unit manufacturing cost decreasing with total sales volume and this in turn impacts on the sale price. As such, reliability, price and warranty decisions need to be considered jointly. The paper develops a model to determine the optimal product reliability, price and warranty strategy that achieve the biggest total integrated profit for a general repairable product sold under a free replacement-repair warranty strategy in a market and looks at two scenarios for the pricing and warranty of the product. The model assumes that the sale rate increases as the warranty period increases and decreases as the price increases. The maximum principle method is used to obtain optimal solutions for dynamic price and warranty situations. Finally, numerical examples are given to illustrate the proposed model.     

Multi-plant assembly planning models for a collaborative manufacturing environment

In a global supply chain, the components or parts of a product may be distributed and produced at various plants in a collaborative way for the purpose of expanding capacity and reducing costs. For an assembled product, the assembly operations for assembling the product may be performed at different assembly plants at various geographical locations. Therefore, in this collaborative manufacturing environment, it is required that one develops a multi-plant assembly planning model for organizing and distributing the assembly operations to the suitable plants for completing the final product. In this research, a multi-plant assembly planning model for generating and evaluating the multi-plant assembly sequences is presented. New graph-based models are developed to model and generate the assembly sequences. The feasible assembly sequences are analysed and evaluated based on several cost objectives. The multi-plant assembly planning model is formulated with the aim of minimizing the total of assembly costs and multi-plant costs. As a result, the optimized multi-plant assembly sequences can be obtained and each of the assembly operations is assigned to the suitable plant with a minimized cost. Example parts are tested and discussed.     

Bayesian risk-based decision method for model validation under uncertainty

This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment.     

Integrated production planning and quality control for linear production systems under uncertainties of cycle time and finished product quality

This work considers serial production systems with several process steps and a possible quality control at final step. It deals with the problem of optimising planned lead time when the real lead time for each process is stochastic and the finished product quality is uncertain unless it is inspected. Three analytical models are proposed aiming to minimise the expected total cost, which is composed of the inventory and backlogging costs for the finished product and quality costs associated with inspection and non-conformities. These models correspond to three quality control policies: (i) without quality control, (ii) with quality control but without taking into account the inspection duration when optimising the planned lead time and (iii) with quality control and with considering the inspection duration when optimising the planned lead time. Based on the results, it can be highlighted the economic advantage of integrating quality control at the early stage of supply and production planning decisions for some cost parameters conditions. The robustness of the proposed models is also analysed regarding the variance of the probability distributions of the lead times.     

Reliability qualification of semiconductor devices based on physics‐of‐failure and risk and opportunity assessment

Qualification frequently is a time‐critical activity at the end of a development project. As time‐to‐market is a competitive issue, the most efficient qualification efforts are of interest. A concept is outlined, which proactively integrates qualification into the development process and provides a systematic procedure as a support tool to development and gives early focus on required activities. It converts requirements for a product into measures of development and qualification in combination with a risk and opportunity assessment step and accompanies the development process as a guiding and recording tool for advanced quality planning and confirmation. The collected data enlarge the knowledge database for DFR/BIR (designing for reliability/building‐in reliability) to be used for future projects. The procedure challenges and promotes teamwork of all the disciplines involved. Based on the physics‐of‐failure concept the reliability qualification methodology is re‐arranged with regard to the relationships between design, technology, manufacturing and the different product life phases at use conditions. It makes use of the physics‐of‐failure concept by considering the potential individual failure mechanisms and relates most of the reliability aspects to the technology rather than to the individual product design. Evaluation of complex products using common reliability models and the definition of sample sizes with respect to systematic inherent product properties and fractions of defects are discussed. Copyright © 2002 John Wiley & Sons, Ltd.     

Peer Review as a QA Tool in Environmental Applications.

Peer Review is commonly applied during the final stage of a project and is used in the science community to determine the soundness of a conclusion and if the quality of information meets the standards of the scientific and technical community. Quality Assurance and Quality Control procedures are most effective when applied to planning, then during the process stage of a project, and during the review of a product. The gold standard for validating the quality of a study's results is comparison with a referenced data set, model, or result (Azouzi, 1999). However, costs can severely limits this approach for many applications. This article proposes an additional means for quality assessment using peer review as a quality assessment tool during the planning, process, and review of a project.     

A techno-economic assessment of an algal-based biorefinery

Economic and technological assessments have identified difficulties with the commercialization of bulk products from microalgae, like biofuels. To overcome these problems, a multi-product algal-based biorefinery has been proposed. This paper performs a techno-economic assessment of such a biorefinery. Four production pathways, ranging from a base case with commercial technologies to an improved case with innovative technologies, are analyzed. All region-specific parameters were adapted to Belgian conditions. Three scenarios result in techno-economically viable production plants. The most profitable scenario is the scenario which uses a specialized membrane for medium recycling and an open pond algae cultivation. Although the inclusion of a photobioreactor decreases the culture medium costs, the higher investment costs result in lower economic profits. The carotenoid content and price are identified as critical parameters. Furthermore, the economies of scale assumption for the photobioreactor is critical for the feasibility of this cultivation technology. The techno-economic assessment is an important methodology to guide and evaluate further improvements in research and shorten the time-to-market for innovative technologies in this field.     

Facility layout design in a changing environment

Increasing global competition, rapid changes in technology and the necessity to respond quickly to a cost and quality conscious customer have changed the dynamics of facilities planning. Today's manufacturing facility needs to be responsive to the frequent changes in product mix and demand while minimizing material handling and machine relocation costs. In this paper, we present a framework for the design of a dynamic facility which can respond effectively to the changes in product design, mix and volume in a continuously evolving work environment. A genetic algorithm-based heuristic is used for solving the design problem and two test cases are presented to illustrate the use of the methodology.     

Robust computer-aided parameter and tolerance determination for an electronic circuit design

Conventionally, parameter design precedes tolerance design in the course of product design or process planning. To lower the production costs, as well as to improve quality, this study proposes the simultaneous determination of parameter and tolerance values when designing an electronic circuit. With the current development of CAD (Computer-Aided Design) software for electronic circuit design, engineers can determine parameter and tolerance values without providing transfer functions for circuit analysis. In this study, a computer experiment is performed by using CAD software (PSpice) to obtain outputs that will be converted into the total cost, which includes the quality loss, the tolerance cost and the failure cost. Then, Response Surface Methodology (RSM) is employed to minimize the total cost and to find the optimal parameter and tolerance values statistically. Consequently, a parameter and tolerance design for quality improvement and cost reduction can be achieved for any complex electronic circuit during the early stages of design.     

基于价值工程的产品优化设计研究

目的 弥补目前价值工程应用到产品优化设计中时,只考虑减少成本,忽视改善质量的局限。方法 运用价值工程的对象选择原则和方法,对预期寿命周期高,已经在市场上销售一段时间的产品进行价值分析,提出初步的设计方向,再通过对某一批次的产品维修记录的统计分析,引入产品功能可靠度的概念,对价值工程提出的设计方向进行修正。结果 将功能可靠度与价值工程的分析相结合,有效弥补传统价值工程指导产品优化设计时,只关注成本而忽视质量的缺点。结论 通过实例进行验证,最终结果表明,功能可靠度与价值工程相结合提出的优化设计方案,在改善产品质量的同时,也有效降低了成本。     

微软WORD格式中的软件质量保证

“在廉价的甜味逐渐减弱消失后,就会倍偿长期持续的苦味。“高质量软件的生命周期成本只是低质量软件的生命周期成本的几分之一。在一些情况下,质量保证的软件对于使用该软件的客户意味着生命悠关。例如,飞行员读了令人误解的荧屏显示就有可能以付出他（她）以及乘客的生命作为代价。软件质量保证方法或过程必须标准化并用于确保软件产品的安全以及成本效果,软件质量保证应占项目总成本的6%。     

Quality control of an unreliable random FMS: with Bernoulli and CSP sampling

It is widely recognized that disassembly-based product End-of-Life strategies, such as component reuse or simple fraction material recycling, are environmentally beneficial. However, current disassembly costs hinder a widespread application of these strategies. This paper quantifies the disassembly time reductions required to achieve economic feasibility of systematic product disassembly. A modelling framework, based on linear programming, is used to investigate the effect of reducing the expected disassembly time and cost on the selection of the optimal End-of-Life strategy. The problem is optimized from an End-of-Life treatment facility point of view. All findings are based on the Belgian cost and price information captured in spring 2004. The linear programming model shows that for small products from the Waste of Electric and Electrical Equipment (WEEE) category disassembly-based End-of-Life strategies will hardly become optimal, while for medium- and large-sized products, this scenario can be made optimal if a substantial disassembly time reduction is achieved. Possible strategies to realize such reduction are briefly sketched.     

System modelling for economic raw material selection

A system simulation method for economic raw material selection is presented, based on a realistic example. The total cost considered in raw materials selection is deemed to include the basic raw material cost, the extra manufacturing cost due to the selection of the particular raw material, and the final product quality cost. These costs are systematically simulated for three typical areas of interest: for the purchasing operation, for the manufacturing process and for the final product quality acceptance by the customer.     

Robust product development for multiple quality characteristics using computer experiments and an optimization technique

Conventional parameter or tolerance designs focus on developing exact methods to minimize quality loss or manufacturing cost. The inherent assumption is that the response functions which represent the link between controllable variables and response values of quality characteristics are known before a design is developed. Moreover, parameter and tolerance values are assumed to be independent controllable variables in previous works; namely, they are determined separately in design activities. Currently, advanced computer software, such as computer-aided engineering, can help engineers to handle design problems with unknown response functions, at the stage of product design and process planning. Therefore, in this study, the software ANSYS was employed to obtain simulation data which represent the response values of quality characteristics. These response values will be used to fit a set of response functions for later analysis. However, previous works in computer simulation for design and planning usually lack consideration of the noise impact from an external design system. To approximate a realistic design environment, various levels of controllable variables, in conjunction with artificial noises created from uncontrollable variables, are used to generate simulated data for statistical analysis via Response Surface Methodology (RSM). Then, an optimization technique, such as mathematical programming, is adopted to integrate these response functions into one formulation so that optimal parameter and tolerance values are concurrently determined, with multiple quality characteristics taken into consideration. A bike-frame design was used to demonstrate the presented approach, followed by multiple quality characteristics of interest: material cost, bike-frame weight, structure reliability, and rigidity dependability. The goal is to minimize material cost and bike frame weight and to maximize structure reliability and rigidity dependability. This approach is useful for solving any complex design problems in the early stages, while providing enhanced functionality, quality, economic benefits, and a shorter design cycle.     

Combined strategic and operational planning – an MILP success story in chemical industry

We describe and solve a real world problem in chemical industry which combines operational planning with strategic aspects. In our simultaneous strategic & operational planning (SSDOP) approach we develop a model based on mixed-integer linear (MILP) optimization and apply it to a real-world problem; the approach seems to be applicable in many other situations provided that people in production planning, process development, strategic and financial planning departments cooperate. The problem is related to the supply chain management of a multi-site production network in which production units are subject to purchase, opening or shut-down decisions leading to an MILP model based on a time-indexed formulation. Besides the framework of the SSDOP approach and consistent net present value calculations, this model includes two additional special and original features: a detailed nonlinear price structure for the raw material purchase model, and a detailed discussion of transport times with respect to the time discretization scheme involving a probability concept. In a maximizing net profit scenario the client reports cost saving of several millions US$. The strategic feature present in the model is analyzed in a consistent framework based on the operational planning model, and vice versa. The demand driven operational planning part links consistently to and influences the strategic. Since the results (strategic desicions or designs) have consequences for many years, and depend on demand forecast, raw material availability, and expected costs or sales prices, resp., a careful sensitivity analysis is necessary showing how stable the decisions might be wit h respect to these input data.     

Computer‐aided tolerance synthesis with statistical method and optimization techniques

Most tolerance design optimization problems have focused on developing exact methods to reduce manufacturing cost or to increase product quality. The inherent assumption with this approach is that assembly functions are known before a tolerance design problem is analyzed. With the current development of CAD (Computer‐Aided Design) software, design engineers can address the tolerance design problem without knowing assembly functions in advance. In this study, VSA‐3D/Pro software, which contains a set of simulation tools, is employed to generate experimental assembly data. These computer experimental data will be converted into other forms such as total cost and Process Capability Index. Total cost consists of tolerance cost and quality loss. Then, empirical equations representing two variables can be obtained through a statistical regression method. After that, mathematical optimization and sensitivity analysis are performed within the constrained ‘desired design and process’ space. Consequently, tolerance design via computer experiments enables engineers to optimize design tolerance and manufacturing variation to achieve the highest quality at the most cost effective price during the design and planning stage. Copyright © 2001 John Wiley & Sons, Ltd.     

Optimal pricing and two-dimensional warranty policies for a new product

For commercial products, pricing and warranty are two crucial marketing strategies, which are used to promote the potential market share. The warranty policy adopted by most of the capital-intensive products, such as machines and automobiles, usually has two dimensions, i.e. warranty age and warranty usage. In this paper, we propose to investigate the profit-maximisation problem, in which the revenue and costs will be affected by the product price and the area of warranty region, for a new product sold under two-dimensional warranty. We assume that the product sales can be captured by a stochastic Bass model based on the nonhomogeneous Poisson process. The product follows a two-dimensional failure process and is covered by a non-renewable free minimal-repair warranty, with age and usage limits. We focus on three revenue/cost components, i.e. sales revenue, warranty cost and production cost, that will significantly affect a firm’s total profit. The profit is maximised by jointly optimising three decision variables, i.e. product price, warranty age limit and warranty usage limit. Numerical experiments are conducted to illustrate the effects of some key parameters, including product reliability, price elasticity, warranty elasticity and learning effect factor, on the optimal settings of the price and warranty region.     

Bayesian belief network-based framework for sourcing risk analysis during supplier selection

Increasing trend in global business integration and movement of material around the world has caused supply chain system susceptible to disruption involving higher risks. This paper presents a methodology for supplier selection in a global sourcing environment by considering multiple cost and risk factors. Failure modes and effects analysis technique from reliability engineering field and Bayesian belief networks are used to quantify the risk posed by each factor. The probability and the cost of each risk are then incorporated into a decision tree model to compute the total expected costs for each supply option. The supplier selection decision is made based on the total purchasing costs including both deterministic costs (such as product and transportation costs) and the risk-associated costs. The proposed approach is demonstrated using an example of a US-based Chemical distributor. This framework provides a visual tool for supply chain managers to see how cost and risks are distributed across the different alternatives. Lastly, managers can calculate expected value of perfect information to avoid a certain risk.     

Strategic evolution of eco-products: a product life cycle planning methodology

This paper presents a methodology and a software tool to establish an eco-design concept of a product and its life cycle by assigning appropriate life cycle options to the components of the product. The product life cycle planning (LCP) methodology provides the following systematic procedures. First, the medium- or long-term production and collection plan for the product family is clarified. Next, target values for the product and its life cycle are set in the process of determination of customer-oriented specification and eco-specification. Then, eco-solution ideas to realize reasonable resource circulation are generated by using various life cycle option analysis charts. Finally, an eco-design concept which involves eco-solution ideas is evaluated for decision-making at early stages of product development. A design support tool was made for efficiently planning product life cycles by using quality function deployment and life cycle assessment data. Based on case studies, it was verified that the proposed methodology and tool are useful for developing multi-generational eco-products.     

Designing a software reliability programme

Designing reliable software is becoming an ever increasing problem because the high cost of software is largely due to reliability problems. The costs of finding and fixing the errors, better known as maintenance and testing costs, account for as much as 80 per cent of the total cost of the final software product. Software developers now have an even greater interest in preventing errors from making their way into the software and finding the errors that are present in the early stages of development. Precise software design, coding and testing play an important role. This paper presents a management plan for implementing a software reliability programme at a small software industry where no reliability programme yet exists and no reliability programme is yet established.