**1. Introduction**

During a product development process, information becomes available to, and is requested by, many partners, design teams and organisations. Information about properties and performance of components and subsystems is the basis of decisions made in the development process. This information has many sources ranging from mathematical models, simulations, testing of physical models and prototypes and customer use data. It has many destinations, in the primary design phase and then through the product life in operations of maintenance, refit and redesign. Product Lifecycle Management (PLM) is primarily concerned to create product

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

models to cover the full range of processes, operations and activities required to support a product through its lifecycle. A critical and current issue is the extent that these product models provide the basis for generating corresponding process models particularly dynamically so that process models continuously reflect the current state of the product models [1]. One aim is to enhance through improvements in workflow for planning product development processes, the significant gains that PLM systems have delivered over a period of 25 years in reducing both the duration and costs of product development [2]. Research by the authors [3, 4] has concentrated on the processes of testing and their ubiquity through product development. Critical testing processes such as field testing ([2], for example) are identified in these workflows, which deliver product development. However, the way that these testing processes form a critical part of all the processes from start to finish of the product lifecycle, whether as inputs, as drivers for iteration, for establishing alignment to regulations or for confirmation of completion of a satisfactory design, has received limited consideration in the literature. Tests are long and expensive activities and most product development activities and tasks depend on the results of test, whether, physical test, simulations or field data gathered during customer operations. This chapter examines methods to integrate testing more closely with other product development processes as well as to improve the planning of the processes of testing so that testing activities are scheduled optimally. Further, the chapter examines how the results of tests can be applied to assist other product development processes. Critically, it analyses how preliminary test results can be of significant assistance to these other processes, speeding their completion.

useful insights into the relationship between the product models of PLM [1, 2] and the process

Testing and PLM: Connecting Process and Product Models in Product Development

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This chapter applies the results of this research to integrate testing and design more widely in the product lifecycle. Section 2 introduces some background and literature of PLM with particular reference to testing. Testing is considered from a general perspective as activities which analyse properties and performance of designs. A short review of existing research on the relationship between testing and PLM in Section 3 covers the mixes of testing activities at various stages of the product lifecycle based on some industry observations. Section 4 extends the proposition, first proposed by Tahera et al. [3] for testing and design, and reviews a three-way mix of testing types comprising simulation, use data (from embedded product monitoring) and physical testing. Further, wider implications of these methods are drawn in Section 5, especially in how PLM systems coordinate product models generated through design, testing and product monitoring activities. Section 6 discusses the tentative nature of these findings, the requirements for further research and the potential benefits for PLM systems. In particular, the refinements in process models recognise testing activities explicitly and their close integration with other processes in product development. Changes in process models drive changes to product models and PLM. This research does not cover the latter

Two observations are relevant when considering testing in product lifecycle. First, testing is a continuing activity, whether physical or virtual, throughout lifecycle. Testing data sets up maintenance schedules and product use data assists in updating these schedules. Periodic refit and redesign may emerge from testing new materials, components and subsystems to

Second, testing supplies information which becomes part of a product description. PLM systems handle several product descriptions [7, 8] and a major challenge is maintaining consistency and integrity of multiple descriptions In the simple case this might mean ensuring that changes to a design in one description, perhaps CAD geometry, are propagated accurately to descriptions for manufacture and assembly such as BoMs and tolerancing schemes. Results of testing update these multiple descriptions in PLM systems. As observed above, testing takes place continuously through product development and product use. However, the schedules

Product performance data is gathered over a range of use conditions and longitudinally over time. Data of two types is relevant in testing. Special tests can be set to investigate particular characteristics such as thermal dynamics of an engine which formed one of the areas of previous research [3]. Other data is gathered from product monitoring in the field. Increasingly the latter data, which may include component wear, degradation in performance or replacement of components, for determining preventative maintenance or redesign of failing components, is well established for complex products such as aerospace [9]. However, quick and effective

models [6] in product development.

**2. PLM data and descriptions**

stages [as referred as End of life (EOL)] of product lifecycle.

track upgrades and changes to customer requirements.

for physical testing activities have long duration.

Previous research by the authors has addressed two particular issues. First, combining information from both physical and virtual testing (simulation) can bring forward in time the availability of a workable product model suitable for the next design stage [3]. This helps planning a design process in an iterative cycle of proposal, test and redesign through developing a method to analyse the overlap between steps in this cycle and optimise this overlap to reduce overall development time. In particular, the long duration of some physical tests, which are necessary to ensure performance and conformance to regulations and standards, are a bottleneck in product development. Starting downstream design activities dependent on these tests before the tests are completed can ease this bottleneck. Essentially, the proposed method applies information from two distinct product models, simulation and physical test to change the process model, allowing significant overlap between activities. The method relies on observing the degree of convergence between simulation and test data.

The second piece of research [4, 5] examines more closely how testing activities can be explicitly integrated into the product development process for complex engineering products. This research highlights the mismatch between several models of product development which tend to relegate testing to be an activity late in the design process or primarily concerned with quality issues. In fact, examination of practice shows that testing is integrated throughout. The misconception in product development process models has possibly arisen because the long duration of physical tests means that the results of testing are not available until later stages, although the activity itself necessarily starts early in the process. This research therefore points to a significant reappraisal of appropriate process models resulting from how data is available in product models. Both strands of previous research have focused on testing for design, rather than wider product development through lifecycle. However, they provide useful insights into the relationship between the product models of PLM [1, 2] and the process models [6] in product development.

This chapter applies the results of this research to integrate testing and design more widely in the product lifecycle. Section 2 introduces some background and literature of PLM with particular reference to testing. Testing is considered from a general perspective as activities which analyse properties and performance of designs. A short review of existing research on the relationship between testing and PLM in Section 3 covers the mixes of testing activities at various stages of the product lifecycle based on some industry observations. Section 4 extends the proposition, first proposed by Tahera et al. [3] for testing and design, and reviews a three-way mix of testing types comprising simulation, use data (from embedded product monitoring) and physical testing. Further, wider implications of these methods are drawn in Section 5, especially in how PLM systems coordinate product models generated through design, testing and product monitoring activities. Section 6 discusses the tentative nature of these findings, the requirements for further research and the potential benefits for PLM systems. In particular, the refinements in process models recognise testing activities explicitly and their close integration with other processes in product development. Changes in process models drive changes to product models and PLM. This research does not cover the latter stages [as referred as End of life (EOL)] of product lifecycle.
