Introduction
Today we live in an era of key transformations in business and society. The industrial sector will accordingly change more in the next few years than in the past decades. This change will build on key advances, leading to a deep implementation of Information and Communications Technology (ICT) and manufacturing technologies in factories, while reflecting the need to face different challenges for business competitiveness and societal and environmental impacts (Filos Citation2017).
Manufacturing will take advantage of the new technological development for many reasons, amongst them are the development of new products, the reduction in time to market, the cost-effective use of manufacturing resources and the provision of personalized products (Romero et al. Citation2020). This requires a paradigmatic approach to take advantage of the convergence of cutting-edge technologies to achieve smart systems in manufacturing facilities. Therefore, innovations will result from the development of materials, processes and products, and the data-driven approaches to support decision-making (Kusiak Citation2018; Tao et al. Citation2018).
To enable Smart Manufacturing, important issues must be considered including interoperability, the development of the technologies themselves, the need to develop an integrated technology and a customization support for the development and application of the technology according to what is needed in practice (Kang et al. Citation2016).
Considering this evolutionary context and in particular the need to have a scientific direction with key impacts on applied science, starts from discussions held within the Intelligent Manufacturing Systems (IMS) Working Group. The IMS Working Group represents a scientific community dealing with the historical move of Intelligent Manufacturing and affiliated to the International Federation of Automatic Control (IFAC) Technical Committee 5.1, namely TC 5.1 Manufacturing Plant Control. The working group is the promoter of the series of IFAC international IMS workshops. First established in 1992, the workshop has been held periodically in many countries. Numerous researchers worldwide contributed to IMS workshops, resulting in productive outcomes over the past three decades.
This Special Issue originates from the IMS 2019 workshop held in Canada and aims to continue the contribution of the IMS Working Group with respect to the transition towards Smart Factories.
The transition towards Smart Factories
The transition is built upon Cyber-Physical Systems (CPS) embedding the technological development addressed by the manufacturing transformation. Different technologies should be considered, starting from Cloud computing and Internet of Things, Big data analytics and Smart sensors amongst the key elements of a CPS-based environment of a Smart Factory, while further technologies should be integrated and applied in the manufacturing process such as Additive Manufacturing and Collaborative Robots or in sophisticated transformation stages such as Virtual/Augmented Reality (Kang et al. Citation2016; Sanchez, Exposito, and Aguilar Citation2020; Nodehia et al. Citation2017). Many factors also play an important role in CPS for manufacturing, leading to different visions including self-organizing manufacturing, context-/situation-aware control, symbiotic human–robot collaboration and turning current shop floors into factories of the future with improved performance (Wang, Törngren, and Onori Citation2015). This transition then outlines the emergence of various characteristics determining the essence of Smart Manufacturing and Smart Factories (Ghobakhloo Citation2018; Napoleone, Macchi, and Pozzetti Citation2020).
Overall, the cyber-physical integration is an essential key enabler. On the one hand, it allows nurturing intelligence and facilitate the exploitation of advanced analytics, modelling, simulation and optimization in manufacturing; on the other hand, it allows supporting the (re)configuration of manufacturing systems embedding advanced manufacturing technologies and advanced automation solutions (Barari et al. Citation2021). The transformation will then impact different target areas. Based on Barari et al. (Citation2021), the Guest Editors consider four key application areas within the Smart Factory, namely Intelligent Design and Manufacturing, Intelligent Process and Production Control, Intelligent Quality Inspection, Monitoring and Control and Intelligent Maintenance.
With this Special Issue, readers are made aware of the co-existence of the ‘smart’ and ‘intelligent’ terms for a while. Today they are used as interchangeable terms as well as specific terms to emphasize different aspects of ‘smartness’ or ‘intelligence’ of advanced manufacturing systems. This conceptual discussion is beyond what is conveyed in this Special Issue, being on the background. Thus, the papers presented in this Special Issue cover different areas of smartness/intelligence of the factory of the future. Besides, it is believed that a special focus may arise while reading the selected papers in regard to the wide range of activities and proposed models, algorithms, frameworks, methodologies and any other artifact that come along with the technology development and application in order to fit the practical needs from manufacturing. Thus, the Special Issue looks at different areas of applications in the Smart Factory, by also covering different maturity stages towards the final deployment in the real factory.
A matrix to classify the research papers
This Special Issue includes 12 papers on variety of topics addressing the transition towards Smart Factories, in the four previously specified categories of Intelligent Design and Manufacturing (4 papers), Intelligent Process and Production Control (4 papers), Intelligent Quality Inspection, Monitoring and Control (4 papers), and Intelligent Maintenance (1 Paper), with some degrees of overlap. One way to reduce the chance of overlapping in classification can be by introducing a second dimension for classification and structuring a 2D classification matrix as the Technology Maturity Stage (TMS).
A very important objective for IMS Working Group is industrial implementation. Typically, a certain level of maturity in the technology development process is needed for industrial implementation. A metric has been defined to address this attribute of the research papers and name it the Technology Maturity Stage. Three stages are defined for TMS as follows:
TMS 1 – Investigation of Knowledge
TMS 2 – Developing Methodology
TMS 3 – Implementation, Assessment and Revision
TMS 1, Investigation of Knowledge, includes research papers that are motivated with the statement of an existing or predictable problem and investigates the foundational knowledge required to solve it. Research papers which utilize the available knowledge and try to develop an approach and methodologies to solve the problem are labeled as TMS 2, Developing Methodology. The third stage, TMS 3, Implementation, Assessment, and Revision, includes research papers with dedication towards implementation of an available solution, assessing its success level and revising it based on practical learnings. Of course, there are research papers that cover more than one TMS or discuss the interface between two TMSs. However, most research papers are typically dedicated to one major TMS as the focus of their study.
The above three stages in technology maturity can also be compared to the Technology Readiness Levels (TRLs) metric. The TRLs were developed at NASA in the 1970s and adopted by various organizations internationally as a metric to measure the level of technology maturity and its readiness for industrial implementation/utilization (Héder Citation2017). TRLs have been employed by various government sectors to measure and allocate time and other resources to research projects (EARTO Citation2014) and, in particular, in advanced manufacturing research to study the requirements for successful implementation of the future of manufacturing technologies (Wang Citation2018). Although the TRLs were originally presented in seven levels, today, various organizations commonly define and adopt nine TRLs with significant similarities (NASA Citation2022; EC Citation2014; Canada Citation2018). presents three versions of the TRLs defined by NASA, the European Union and the Government of Canada as examples. It can be seen that TMS 1 covers the first two TRLs, TMS 2 covers TRLs 3 to 5 and TMS 3 includes TRLs 6 to 9.
The details provided by the nine TRLs are suitable for the purpose of managing the research project and allocating funds, time and other resources to them; for our objective, which is the classification of the research papers, these details do not seem needed. The reason is that it is interesting also to see how a research paper addresses the research activities that belong to multiple TRLs: in most cases, a research paper can be easily assigned to a unique TMS and in some cases to two, whereas it would be rare to see a research paper addressing equally all three TMSs.
The structure of this special issue
The 12 contributed papers are sorted first based on their TMS and second based on the four key application areas. This sorting mechanism defines the order in which the papers are presented in this Special Issue.
The first paper on the design of macro/microtubes using Functionally Graded Materials (FGM) is classified as TMS 1 with application area in Intelligent Design and Manufacturing. The second paper on intelligent machining is classified as TMS 1 in the area of Intelligent Process and Production Control. The third paper, on remaining useful life prediction in Industry 4.0 manufacturing systems, is also in category TMS 1; however, its application area is Intelligent Maintenance.
The TMS 2 papers are from the fourth to the seventh papers. The fourth paper on fault-tolerant control and the fifth one on irregular packing problem are considered having applications on Intelligent Process and Production Control, and the sixth paper on error modelling of a coordinate metrology robot and the seventh paper on processing the large sets of digital metrology data are considered with applications on Intelligent Quality Inspection, Monitoring and Control.
The five remaining papers are in TMS 3 category. The eighth paper on training and commissioning of industrial bin picking systems and the ninth paper on process planning for additive manufacturing of thin-wall domes are with applications on Intelligent Design and Manufacturing. Cobot task allocation on an actual assembly line presented in the tenth paper has applications in both areas of Intelligent Design and Manufacturing and Intelligent Process and Production Control. The eleventh paper on tool path error modelling of an existing parallel mechanism for milling and the twelfth paper experimenting on the effect of parameters controlling a laser powder bed additive manufacturing process have applications in the area of Intelligent Quality Inspection, Monitoring and Control.
Conclusions
This Special Issue has been developed based on the contributions of IMS Working Group with the overall attention to the requirement for transition towards Smart Factories. In this editorial, the objectives and structure of the Special Issue are discussed and a 2D matrix is presented for the classification of research papers in this domain.
References
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