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Chapter 3 System Framework of PCS for CMfg

PCS was in existence for decades and its technology has matured, providing the industry with a set of usability standards and best practices. However, even the state-of-the-art PCS performs poorly in terms of connectivity with production systems and supply chains. This issue has hampered the automation of highly personalised product configuration (e.g., ETO product). To facilitate the efficiency of fabricating highly personalised products and effective manufacturing collaboration in a distributed manufacturing environment, CMfg aims to construct a global service-oriented manufacturing environment by virtualising and encapsulating manufacturing resources and capabilities. In this regard, this chapter first studies how to utilise CMfg technologies to enhance the connectivity issues of PCS. Since very little research has addressed conducting product configuration activities in a service-oriented manufacturing paradigm, the author proposes the concept of product-service family (PSF) to enable holistically integrated configuration (HIC) in CMfg. In PSF, a “service twin” for modular-designed product is built to extend the configuration model from product domain to service domain. After that, to implement PCS in CMfg (CM-PCS), a system framework of PCS in CMfg is presented.

Methodology for System Development

On the foundation of literature review, the general target of this research – to develop of the next generation PCS can be accomplished by planning a system framework and constructing the framework on basis of proper approaches. To be specific, the methodology of this research consists of 4 steps (see Figure 3.1):
(1) Design a framework for constructing PCS in CMfg
In consideration of service-oriented architecture of CMfg, the system framework of PCS in this research should be extended to service domain to integrate manufacturing cloud. Based on the integration, PCS can utilise services and cloud-sourced knowledge to facilitate integrated configuration and distributed configuration. To achieve that, service-oriented architecture will be adopted for the construction of framework.
(2) Configuration knowledge modeling
“Integration” is the key word for system development in this research. On one hand, the author strives to enable integrated configuration of product, process and supply chains. On the other hand, the integration of distributed companies in a configuration activity should be carried out through the introducing of CMfg model. In such a situation, a comprehensive configuration knowledge model is essential to achieve integration by documenting product knowledge, process knowledge and cloud-sourced knowledge. Since CMfg environment is dynamically changing based on the availability of service providers, knowledge model for configuration cannot stay static. For this reason, ontology-based approach will be used to enable configuration knowledge evolving. Besides, considering the complexity of process information (e.g. machining process), STEP-NC will be ontologically coded to enrich the ontology-based knowledge model.
(3) Optimisation for the boundary of configuration problem solving
To reduce the workload of configuration reasoning and ensure the fulfilment of configuration results, the boundary conditions of product configuration activities should be optimised. Due to the complicated partnership between service providers in CMfg environment, augmented Lagrangian coordination (ALC) algorithm is chosen for optimisation.
(4) UX enhancement
Apart from focusing on the downstream in product configuration process, this research also looks upstream to enhance UX in the development of PCS. The enhancement is conducted in two ways. First, ask customer to determine the DCF of configuration process rather than offer them one set of configurable options. Second, adopting advance visualisation technologies – VR to establish an immersive configuration portal for users. To evaluate these two measures, a human ethic experiment will be conducted.
Based on the 4-step roadmap, the methodology will start with the framework which is groundwork of this research.

Holistically integrated configuration

Increasing demands on the connectivity of PCS are propelling the adoption of advanced Internet and computing technologies among the venders of product configuration tools. Through connecting with enterprise systems in manufacturing networks, the manufacturability of customer requirements (CRs) in the configuration process can be verified easily. To automate product customisation in various order fulfilment strategies, a novel way of holistically integrating product, process and supply chain in dispersing manufacturing network is presented.

Connectivity of PCS

Technologies of product configuration have matured for decades. Although pioneer configuration tools were designed as stand-alone systems, researchers have realised the significance of integrating configuration applications with other systems since the early 1990s [43]. The early endeavours to facilitate integration mainly focus on bridging configuration tools and data-modelling systems (e.g., PDM) to settle the issue resulted from frequently changing product data. Besides, many configuration application vendors (including CAD software companies) were rushing to develop CAD integrated configuration solutions at that time. To this day, parametric graphical configuration (PGC) (i.e., change configurable design parameters by directly manipulating 2D or 3D product model such as Configura [133]) is still characterised as a significant feature for most product configuration management systems. Today, configuration applications are getting more and more features by introducing advanced smart technologies, such as machine learning and cloud computing. Some state-of-the-art product configuration solutions can offer interactive 3D GUI (e.g., KBMAX configuration tools [134]), multi-device access via cloud (e.g., Autodesk Configurator 360 [135]), integration with CRM systems (e.g., Salesforce CPQ [136]), and so on.
Although the advancement of configuration technologies has provided PCS with connectivity to systems like CAD and CRM, the integration is confined to front-end which only includes systems for product modelling, finance, customer engagement, inventory management etc. In fact, no existing industrial practice can address the “information island” problems regarding PCS’s connectivity to manufacturing systems and supply chains. This issue has led to current configuration tools being unable to respond to changes from manufacturing sectors and suppliers in an effective and efficient manner. Therefore, disruptive technologies are critical to break the bottleneck of the “information island” in the development of product configuration applications.

Merging of holistically integrated configuration

As mentioned in Section 2.1, integrated configuration is an effective strategy for supporting in-depth customisation and reducing the lead-time and cost of product development. Meanwhile, distributed configuration focuses on integrating the configuration of end-products and the sub-configuration of sub-products (i.e., subsystem or component). Although both concepts concentrate on integration, the former places more emphasis on the fulfilment of product configuration and the latter stresses collaboration in configuration for complex products. Hence, the author believes that the two approaches are not conflicting, but complementary. To cope with diversifying customer needs and the trend of dispersing manufacturing networks, the synergy of these two methods is increasingly more important. To achieve this, in this research, the concepts of integrated configuration and distributed configuration are merged as holistically integrated configuration (HIC) by borrowing the concepts of horizontal integration and vertical integration from the business sector.
From a business perspective, horizontal integration occurs when accompany acquires a similar company in the same industry, while vertical integration occurs when a company acquires a company that operates either before or after the acquiring company in the production process [137]. In the case of HIC (see Figure 3.2), the product configuration system will integrate both inter-company resources (vertical direction) and intra-company resources (horizontal direction). Through integrating vertically and horizontally, PCS will be connected to each link in the manufacturing process. This connectivity will make PCS capable of: (1) supporting rapid and accurate quotations which is crucial for engaging customers, (2) providing more configurable options for heterogeneous user groups, and (3) facilitating the fulfilment of customising complex product through multi-company cooperation. Through integrating in a holistic way, HIC is capable of coping with order fulfilment strategies ranging from ATO to ETO. Especially for highly personalised products such as ETO product, a full-fledged configuration system that supports HIC is a necessity for carrying out configuration in a distributed manufacturing environment.
Despite these benefits, realising HIC requires not only efforts towards both integrated configuration and distributed configuration, but also the escalated complexity of solving configuration problems in terms of knowledge representation, information exchange, and computation load. In fact, the model of HIC seems unlikely to be achieved in traditional manufacturing and business models. Considering that the nature of CMfg optimises manufacturing resources in response to dynamic demands of product customisation, the author thus adopts CMfg, a new emerging paradigm, to address the challenges in HIC.

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Product configuration in CMfg

CMfg is a service-oriented model of networked manufacturing. Benefiting from virtualisation technologies, a pool of virtual manufacturing resources can be constructed to allow manufacturers to share and integrate manufacturing resources and knowledge to provide configurable services with less management effort. Therefore, CMfg is considered as a disruptive model to facilitate in-depth customisation with time and cost efficiency. This research will study CMfg’s impact on PCS and then analyse the potential of realising HIC with the help of the manufacturing cloud.

Connecting PCS with clouds

Information and computer technologies, in recent years, have become the enabler of the revolution of manufacturing paradigms. Due to those IT advancements, most new emerging manufacturing models (e.g., collaborative manufacturing and networked manufacturing) stress integrating distributed manufacturing resources. As an emerging mode, CMfg not only puts more emphasis on both integration and reconfiguration of distributed manufacturing resources, it also supports resource sharing in a more open environment [29, 32, 33]. The main concept of CMfg is virtualising manufacturing resources as consumable services [34], so the proper composition and reconfiguration of those services are critical to meet the various demands of service consumers. In summary, with the help of CMfg, manufacturing resources are encapsulated as consumable services in the manufacturing cloud and are easily reconfigurable to fulfil personalised manufacturing tasks. Although CMfg has received an increased amount of attention in recent years, the research on product configuration in CMfg or other service-oriented manufacturing models is scarce [138]. Therefore, firstly, how CMfg will affect product configuration will be discussed.
Through the CMfg platform, service consumers can raise customised service requests and the platform will perform service scheduling to realise the service order. Therefore, introducing CMfg into PCS could simplify the production configuration process by replacing process planning with service planning. As Figure 3.3 shows, on the basis of the concept of MaaS, PCS can get access to encapsulated services by interacting with the manufacturing cloud. This research abbreviates a CMfg enabled PCS, as CM-PCS.
In the diagram (see Figure 3.3), PCS is also able to harness other cloud-based applications ranging from CAD to CRM. In fact, the model of SaaS has been commonly adopted by enterprise system vendors. As increasingly more applications have been ported into cloud (e.g., cloud-based CAx and ERP systems), many emerging product configuration applications have been designed as cloud-based systems. Some of these cloud-based solutions have utilised other systems’ API to improve product performance and gain a competitive edge. For example, SteelBrick CPQ [136] is a PCS developed to accommodate Salesforce cloud-based CRM systems. As the trend is towards centralised hosting of business applications in the cloud environment, the integration of CPS with front-end and back-end systems, in the cloud, is the future. These cloud technologies and CMfg will boost the connectivity of PCS.

HIC in cloud environment

As mentioned, HIC can enable the configuration of highly personalised products. In service-oriented manufacturing environments, such as CMfg, the integrated configuration strategy is different from the scenarios in conventional manufacturing models. Due to the characteristics of servitisation, the integrated configuration of product, process and supply chain will be converted into configuring product, process, service and service provider in CMfg. For multiple product configuration activities performed in dispersing companies, porting the distributed configuration systems to cloud environment under the coordination of CM-PCS and CMfg platform will be a solution. This is because virtualised manufacturing resources of all the involved dispersing enterprises are managed in a centralised way by the CMfg platform. Such centralisation can be categorised into two levels:
Configuration knowledge level. As the first scenario illustrated in Figure 3.4, instead of building discrete systems as is the traditional strategy of distributed configuration, the configuration knowledge from dispersing companies is merged and managed in centralised fashion. This strategy requires a certain adaptability and homogeneous structure for these configuration models. Approaches such as ontology-based knowledge bases will reduce the difficulty of merging knowledge.
Configuration task level. As shown in the second scenario in Figure 3.4, similar to a traditional distributed configuration framework, the configuration knowledge from dispersing manufacturers will be inferred in separate sub-configuration tasks. This type of distributed configuration is more suitable for heterogeneous knowledge bases.
It is noteworthy that the configuration results (e.g., BOM contains product design and process information) will be utilised for retrieving proper services in the CMfg platform. Therefore, establishing a mechanism for IP protection is a necessity in product configuration in CMfg. The strategies to control IP leakage have been studied in [40].
By connecting with the manufacturing cloud (i.e., CMfg platform), PCS can have access to manufacturing services in the configuration process for distributed manufacturing collaboration across ubiquitous virtual enterprises. In this situation, based on updating resource availability information, the CMfg platform could be able to adjust service provision plans for product configuration activities. This is a huge achievement for personalising a product, especially for ETO product which needs engineering efforts. For example, traditionally, processing a configuration with ETO changes usually costs several iteration cycles for communication between each layer of participants in the personalisation process (as shown in the left section of Figure 3.5). In this process, communication is a necessity to meet both customer expectations and the manufacturability of personalised product. Nevertheless, the “endless loop” consumes a lot of effort, time and money. This is also the reason why the typical applications of an ETO configuration system lie in project-based business such as construction, infrastructure building, ship building, factory design and conveyors. Through the introduction of CMfg, distributed resources from manufacturers are virtualised and integrated to share over the internet. Based on advanced web development technologies (e.g., cloud computing, web service, and semantic web), customers can directly personalise even ETO product by simply communicating with the manufacturing cloud via the portal of CM-PCS (see the right section in Figure 3.5).
In the scenario of product configuration in CMfg, customers, manufacturing firms and suppliers act as service providers and are integrated by CM-PCS. In such a case, based on CRs, CM-PCS can easily react to non-engineering changes by retrieving the availability of corresponding services. Engineering changes will be rapidly analysed, and propagated changes in manufacturing systems and supply chains will be evaluated based on cloud-sourced knowledge. To achieve that, the first critical step is involve service factors in the product configuration process. The following section will establish the relationship between product and service.

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Product-service family

To realise HIC in CMfg, the first challenge is encapsulating virtualised manufacturing resources as services and then orchestrating them to fulfil a configuration based on customer preferences. This section will systematically study service encapsulation and composition for product customisation in a CMfg environment. To achieve HIC, an approach named product-service family is proposed to address the mapping relationship between product domain and service domain.

Service encapsulation for product customisation

In a CMfg environment, packaged manufacturing resources and capabilities can be managed and manipulated by the CMfg platform. The process of packaging, in essence, is the service encapsulation [29]. The key to the encapsulation process lies in the completeness of encapsulated results which should meet both demands from users and quality of service (QoS) by not only providing associated resources (e.g., manufacturing equipment) but also satisfying specific capability requirements (e.g., process planning requirements) [30]. Fundamentally, manufacturing capability aims to transform customers’ requirements into physical products; to achieve that, meanwhile, proper manufacturing resources need to be specified [139]. Most researchers tend to cope with service encapsulation in a manufacturing resource-centred way [139, 140]. To be specific, these researchers cope with customisation requirements by retrieving and compositing services which only contain descriptions of resources (e.g., tools, labour, etc.) without considering what kind of product, component or part they can deal with. Theoretically, virtualised manufacturing resources and capabilities should be encapsulated to address the order of customised product. Therefore, the traditional encapsulation process will affect the completeness of service and may cause unsatisfied demands on manufacturing capacity (i.e., providing equipment for machining without meeting the detailed process-planning requirements of the customisable product). Such incompleteness will result in matching errors between service consumers and service providers and affect user satisfaction [141]. For these reasons, this study focuses on the encapsulation of CMfg service from the perspective of product.
Products, namely objects to be manufactured, are realised by consuming and utilising a series of manufacturing resources and capabilities. Therefore, from a product-centric view it is easy to determine the content and boundary of desired services which contain all needed manufacturing resources and capabilities to fulfil the production. Since the configurable product is comprised of a hierarchy of modules ranging from manufacturing feature to assembly, the encapsulation should consider granularity issues.

Table of Contents
1.1 Research background
1.2 Identifying the challenges
1.3 Objectives and scope
1.4 Thesis organisation
2.1 Cloud manufacturing (CMfg)
2.2 Product configuration paradigms
2.3 PCS technologies
2.4 Smartness and servitisation of product
2.5 Research gaps and motivations
3.1 Methodology for System Development
3.2 Holistically integrated configuration
3.3 Product configuration in CMfg
3.4 Product–service family
3.5 System framework for CM–PCS based on PSF
3.6 Summary
4.1 Ontology development for CM–PCS
4.2 Construct ontology–based CM–PCS
4.3 Adaptability and scalability of CM–PCS: A Case Study
4.4 Summary
5.1 Optimisation for Scalability in CM–PCS
5.2 CS optimisation
5.3 ALC–based CS optimisation
5.4 Summary
6.1 Smartness, service and UX in product personalisation
6.2 Personalisation of smart service product (SSP)
6.3 UX–enhanced SSP personalisation process and case study
6.4 Summary
7.1 Recap of the research
7.2 Scientific contributions
7.3 Limitations
7.4 Recommendations for future work
Product Configuration System for Cloud Manufacturing

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