Framework evaluation results

5.3.3.1 Fit and value of KR in frameworks

Both of the frameworks in the literature demonstrate and clearly describe the benefits of using ontologies in their works and are also clear in describing how they are used. However, Alsafi and Vyatkin (Alsafi and Vyatkin, 2010) the specification layer includes both XML and OWL files, while Lanz (Lanz, 2010) attempts to keep ontological models separate to XML files with them interacting through mappers. In this work, the framework shares some similarities with Lanz (Lanz, 2010) with respect to the fit of the ontologies, and sees the work in Alsafi and Vyatkin (Alsafi and Vyatkin, 2010) to be a significantly narrower in vision and thus reducing the value of implementing the ontology within the framework. The framework significantly extends what has been proposed by implementing a Semantic Exchange layer which is not limited by a specific type of data format (although XML is used to demonstrate it) as is the case with the other frameworks. As aforementioned the consideration for broader standards to integrate the tools with the ontology leads to a more generally usable and thus valuable framework.

5.3.3.2 Contribution of the framework to the engineering workflow

Alsafi and Vyatkin (Alsafi and Vyatkin, 2010) contributed to the workflow at the reconfiguration phase of a manufacturing system while Lanz (Lanz, 2010) was more

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focused on knowledge retrieval which could exist at any phase. Due to the deployable nature of the work carried out by Alsafi and Vyatkin (Alsafi and Vyatkin, 2010) there was more value added as a consequence of using the framework as compared to Lanz (Lanz, 2010), despite its narrower application. This work demonstrates a framework that contributes strongly through multiple lifecycle phases across multiple domains and considers both the existing engineering workflow and the way that the generated knowledge is managed in a way that complements industrial practices. The framework allows the retrieval of knowledge, ascertaining the consistency across domain models, and also rectifying such inconsistencies through parametric or logical changes. This is demonstrated by the queries in Case Study 2 that appreciate the nature of the information that would need to be queried at a given lifecycle phase, within a given domain, and how information would flow through the ontology in a way that mimics the human interrogation processes.

This section of the evaluation therefore surmises that an extension to what has come before with respect to frameworks to support the engineering workflow with ontologies, has been achieved through the research in this thesis.

5.3.3.3 User interaction with the framework

The framework presented by Alsafi and Vyatkin (Alsafi and Vyatkin, 2010) did not explain how users would interact with the model with the assumption being that the entire process would be automated. Lanz (Lanz, 2010) hints at some level of user interaction by mentioning tools that are integrated with the framework. However, in the framework presented in this thesis, there is a substantially clearer demonstration of how and why users would interact with the framework and the ontology more specifically.

In addition, due to the integration with a component-based virtual engineering environment, changes can be assessed before being implemented. The “component-based” element is important to recognise as it does not reflect the industry standard for engineering software. This prevents industrial engineering tools from being extensible and thus preventing a number of key concepts represented within this approach, particularly the Skill model, from being implemented directly into conventional engineering tools. On the other hand, the vueOne toolset can be extended and the respective Skills form an attribute of the different component types, be they ProductComponent, ProcessComponent, or

ResourceComponent. Therefore, to realise Objective 3 it was identified that the framework developed cannot benefit industrial needs unless either software vendors embrace a more open approach and reveal the nuances of their models, or a significant effort is undertaken

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to understand the data models and map the concepts to neutral exchange standards such as AML. The framework accommodates both scenarios, but does rely on the work of future researchers for full implementation.

The “virtual engineering environment” integration facilitated a “zero-risk” nature of experimenting with changes. This was not present in Alsafi and Vyatkin’s (Alsafi and Vyatkin, 2010) work where the intention appeared to be direct deployment of modifications with the assumption that risks had been mitigated through reasoners. However, in the framework in this thesis, steps and logic can be tested without affecting the real system until necessary. Although existing industrial virtual engineering tools for system modelling offer the ability to model changes, the prerequisite remains that the user is operating within the Resource domain i.e. there is no link with high level process descriptions. As a result, changes within one domain must be transformed through domains by human intervention, this can lead to errors as a result of miscommunication. Thus, this work demonstrates how ontological models can be “used” within practical engineering workflows.

5.3.3.4 Additional remarks

5.3.3.4.1 Relevance to PLM

In the literature review chapter, the shortcomings of PLM was identified and it was noted that the research work in this thesis would need to compare with such solutions. The conventional PLM tool chain has suffered from information loss as the lifecycle progresses. Furthermore, there is (as the name suggests) a heavy focus on product information within this paradigm. As a result, the respective tools and methods that have emerged as an outcome of attempting to align themselves within this paradigm have taken to a similar design philosophy. Tools that the author would class within the Resource domain lack the expressivity required and typically do not integrate well with other Resource domain tools. On the other hand they do retain a substantial amount of Product domain information e.g. geometry, material characteristics (Demoly et al., 2011, Lee et al., 2011b) etc. The significance of this within the context of this research is the PLM paradigm and the PPR approach are not aligned. This means that should an integration framework of the nature presented in this work be successful for an industrial application, it would be necessary for an alignment procedure to be carried out and some efforts to bring PLM and PPR together. This challenge has been identified by a number of academics and there are ongoing projects that aim to facilitate the exchange of data between PLM and PPR to address this (El Kadiri and Kiritsis, 2015, Matsokis and Kiritsis, 2010, Milicic et al., 2013, Choi et al., 2010).

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The globalisation of manufacturing enterprises means that those designing the product do not sit in the same geographical location as those considering the process, nor those that design and commission the system. Furthermore, the manufacturing system itself may well be in a different country. The exchangeability of data formats such as XML in conjunction with semantic web technologies present a solution to this problem because OWL models can be published on the World Wide Web thus providing access to anyone with a web browser. This is not typically the case for engineering tools and thus supports more distributed engineering activities. However, OWL has seen limited implementation within industrial settings, particularly in manufacturing, despite its robustness. This has been proved in a number of works, particularly in large EU funded research projects that are summarised in Chapter 2. Despite the strength of the language, the tools used for implementation e.g. Protégé, remain largely the plaything of academics. Furthermore OWL 2, which is the most recent version of OWL, was published in 2012. The language has not had the time to proliferate through the education system and thus there is a lack of expertise to realise implementation. Thus, despite the benefits of the approach demonstrated in this work, the move into an industrial environment is hampered by a lack of expertise and tools.

Summary

The evaluation of any piece of research is fundamental in determining whether or not any novelty exists and there is a significant contribution to the body of knowledge. In this chapter, the author has evaluated the ontology through metrics and a method derived from the literature, and the broader framework based on the objectives of this thesis. An application evaluation was carried out in the preceding chapter based on case studies. The key points from the ontology evaluation are a more adaptable, cohesive, concise, and complete model than has been previously presented in the literature that brings together domain models with an independent Skill model spanning the domains. From the framework evaluation the author identifies that a greater level of value can be derived as compared to previous similar frameworks based on its broader scope and usability. The following chapter concludes the work and based on the gaps and shortcomings identified proposes future steps.

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Conclusion and Further Work

Introduction

As the paradigms of mass customisation and product personalisation become ever prevalent, it is clear that the challenges facing the industry today are accommodating these dynamic market conditions while maintaining profit margins and productivity. At the highest level the questions were to understand why making changes was problematic, and why existing methods for representing knowledge were not addressing the needs of the industry? Following this, the author wanted to address what knowledge models and broader frameworks should look like to support the uncertainty facing manufacturers today. To address these issues, the objectives of the thesis were as follows:

1. Identify change management methods within the context of manufacturing and engineering changes and the challenges that are faced

2. Identify the ontological models that have been developed in the literature and how they have been applied as well as their shortcomings

3. Develop a set of PPR ontologies that can be used to support assembly automation systems engineering through its lifecycle

4. Develop a framework that integrates engineering tools, methods, and workflows with an ontological model

5. Demonstrate how ontologies can be used in a practical way to identify and resolve inconsistencies

These objectives can be classed into two categories. The first category is for objectives 1 and 2 and is the identification of knowledge gaps and shortcomings of existing works that address the same problems. The second category is for objectives 3, 4, and 5 and define the key contributions of this work.

Summary of knowledge gaps