Concurrent Engineering

Overlapping between development activities stemming from concurrent engineering may not only reduce duration of a project but also create rework risk. This article presents a process modeling and analysis technique for managing complex product development projects using optimization and simulation techniques. In order to analyze the forced overlapped process with lead–risk, we propose evolution and sensitivity design structure matrix for reflecting overlapping and their impact on the degree of activity sensitivity and evolution in the process model. Using the design structure matrix, we present the schedule and cost model associated with iteration, overlapping, and rework by incorporating many more general characteristics of complex design processes. The model can be used for better project planning and control by identifying overlapping and risk for process improvements, and for evaluating alternative planning and execution strategies. An industrial example, a tactics aerocraft preliminary development design process at a company, is provided to illustrate the utility of the model using optimization and discrete-event simulation. The optimization model maximizes the compressed time associated with overlapping and yields several managerial insights, including optimization analysis of project activity sequence, how overlapping and rework risk impact on project schedule and cost, trading off schedule and cost risk.

Responding to the need for enhanced software quality, software manufacturers have recently applied quality improvement techniques to software development process. Software quality function deployment, as a technique for better quality designs that match customer expectations, has been used in software development to maximize customer satisfaction. This article proposes a fuzzy regression-based decision framework that considers future requirements for setting target levels of technical attributes in software quality function deployment. Ordered weighted averaging operators are employed to implement quantifier-guided aggregations that enable to calculate the integrated importance degree for each customer need by combining the current and future voice of customers. Then, a fuzzy optimization model, which considers the integrated importance degrees of customer needs and uses the functional relationships obtained by fuzzy regression, is developed to determine target levels of technical attributes of the new or improved software products that meet customer needs at the time when the product reaches the market. The fuzzy optimization model includes both the center values and the spread values of the parameter estimates and thus circumvents loss of information in determining target levels of technical attributes. A search engine quality improvement problem is presented to illustrate the proposed decision framework.

Within the context of build-to-order or assembly-to-order production strategy, an end product satisfying the requirements of a customer often comprises various components or parts that may be provided by the partnering suppliers. More probably, there exist a numerous number of alternative components or parts to be chosen when an end product is configured. Meanwhile, structures and constraints within the configurable product must be observed. To represent structures of products and constraints, object-oriented modeling method is employed to enable the share and reuse of configuration knowledge. To derive optimal configuration, product configuration problem with object-oriented configuration knowledge is formalized as a mixed-integer programming problem. The algorithm for product configuration optimization is implemented using Java CPLEX. Experiments are conducted to demonstrate and compare the performance of the algorithm. The results show that the computational time is reasonable and acceptable for medium-sized configuration problems.

E-quality is a holistic approach to gauge and ascertain product quality in real time with the use of advanced technologies. E-quality manifests a sensor-based, networked, fully automated quality control, through which a reduction of inspection time is attained. Even with the e-quality, a part classification still remains as one of the most challenging tasks because the classification is based on the minute differences among a multitude of dimensional attributes. Part classification entails many steps that complicate the accuracy of final outcome. Achieving 100% classification accuracy is not a trivial matter. In this context, this study focuses on a novel approach for improving part classification accuracy in tune with the notion of e-quality and concurrent engineering. Two approaches are proposed and compared with the traditional multiclass support vector machine classification method. One of the approaches is to modify the data before applying the support vector machine. The other is a completely new Sine methodology using dimensional index values for classifying parts into different categories. Support vector machine is employed due to its higher generalization ability, especially when the data set is small and the class overlap is nonexistent. The data extracted from a machine vision system in a networked robotic inspection cell is used to test the proposed approaches. Experimental results show that the new Sine methodology performs better than the others, displaying near 100% classification accuracy.

A case study of an aircraft engine manufacturer is used to analyze the effects of management levers on the lead time and design errors generated in an iteration-intensive concurrent engineering process. The levers considered are amount of design-space exploration iteration, degree of process concurrency, and timing of design reviews. Simulation is used to show how the ideal combination of these levers can vary with changes in design problem complexity, which can increase, for instance, when novel technology is incorporated in a design. Results confirm that it is important to consider multiple iteration-influencing factors and their interdependencies to understand concurrent processes, because the factors can interact with confounding effects. The article also demonstrates a new approach to derive a system dynamics model from a process task network. The new approach could be applied to analyze other concurrent engineering scenarios.

In collaborative designs that are either intracompany or intercompany, data security and integrity validation are two major concerns. Even though design views can be used effectively for access controls, view updates may cause violation of integrity constraints defined for the base designs. This article focuses on the validation of integrity constraints after view updates. Following standard for the exchange of product model data methodologies, information model is defined by EXPRESS and views are defined by EXPRESS-X. Shared design data are stored in a relational database system (e.g. Oracle 11g XE). The integrity constraints defined in EXPRESS schema are translated into UNIQUE and CHECK and triggers in SQL. Then, they are automatically validated after view updates. Because the paradigm presented in this article is based on open standards such as EXPRESS, EXPRESS-X, and SQL, it is independent from any proprietary system and suitable for collaborative design environments that consist of heterogeneous systems.