Ebook: Advances in Manufacturing Technology XXXV

The International Conference in Manufacturing Research (ICMR) is a major event for academics and industrialists who are engaged in manufacturing research. Held annually in the UK (except 2018 in Sweden) since the late 1970s, the conference is renowned as a friendly and inclusive platform that brings together a broad community of researchers who share a common goal: developing and managing technologies and operations that are key to sustaining the success of manufacturing businesses. For over two decades, ICMR has been the main manufacturing research conference organized in the UK, successfully bringing researchers, academics, and industrialists together to share their knowledge and experiences. Initiated as a National Conference by the Consortium of UK University Manufacturing and Engineering (COMEH), it became an International Conference in 2003.

COMEH is an independent body established in 1978. Its main aim is to promote manufacturing engineering education, training, and research. The Consortium maintains a close liaison with government bodies concerned with the training and continuing development of professional engineers, while responding to the appropriate consultative and discussion of documents and other initiatives. COMEH is represented on the Engineering Professor’s council (EPC) and it organizes and supports manufacturing engineering education research conferences and symposia. Hosts for National Conferences on Manufacturing Research (NCMR) have been:

1985 Nottingham

1986 Napier

1987 Nottingham

1988 Sheffield

1989 Huddersfield

1990 –

1991 Hatfield

1992 Central England

1993 Bath

1994 Loughborough

1995 Leicester De Montfort

1996 Bath

1997 Glasgow Caledonian

1998 Derby

1999 Bath

2000 East London

2001 Cardiff

2002 Leeds Metropolitan

Hosts for the International Conference on Manufacturing Research have been:

2003 Strathclyde

2004 Sheffield Hallam

2005 Cranfield

2006 Liverpool John Moores

2007 Leicester De Montfort

2008 Brunel

2009 Warwick

2010 Durham

2011 Glasgow Caledonian

2012 Aston

2013 Cranfield

2014 Southampton Solent

2015 Bath

2016 Loughborough

2017 Greenwich

2018 Skövde, Sweden

2019 Queen’s University Belfast

2020 – (Pandemic)

2021 Derby

2022 Derby

Industry 4.0 technologies and digitalised processes are essential for implementing smart manufacturing within vertically and horizontally integrated industries. These technologies offer new ways to generate revenue from data-driven services and enable predictive maintenance based on real-time data analytics. Although the fourth industrial revolution has been underway for more than a decade, the manufacturing sector is still grappling with the process of upgrading manufacturing systems and processes to Industry 4.0-conforming technologies and standards. Small and medium enterprises (SMEs) cannot always afford to replace their legacy systems with state-of-the-art machines. One option available in such cases is known as retrofitting, in which manufacturing systems of past generations are upgraded with sensors and IoT components to integrate them into a digital workflow across the enterprise. Unfortunately, the scope and systematic process of legacy system retrofitting and integration are not yet well understood and currently represent a large gap in the literature. In this article, the authors present an in-depth systematic review of case studies and available literature on legacy system retrofitting. A total of 32 papers met our selection criteria and were particularly relevant to our topic. The results identify three digital retrofitting solutions.

Industry 4.0 (I4.0) is an emerging concept describing the business setting application of a broad set of digitalisation technologies, connectivity, and automation. The most common critical infrastructure (CI) uses Industrial Control Systems (ICS) for operation and supervisory control. However, the Supervisory Control and Data Acquisition (SCADA) and Internet of things (IoT) systems are examples of ICSs applications. These systems, like any other systems exposed to many security risks and are vulnerable to many threats. This is mainly due to the lack of objective standards and proactive security countermeasures that companies unintentionally neglected in the early stages of designing these systems. It is also due to the absence of managerial and technical skills necessary to implement them. Therefore, identifying and preventing potential security threats against CIs is the focus of this paper. A novel security approach concept that can predict cybersecurity threats based on the CI nature and take into consideration the attack motivations accordingly has been delivered in this paper. The proposed concept of this approach will also facilitate the detection of potential attack types and the required countermeasures in particular infrastructures.

Industry 4.0 (I4.0) is not an exceedingly new concept. Since the term was coined in Germany in 2011 it has come to encompass many enabling technologies around the digitalisation of manufacturing processes growing further into the service industry and beyond. The need for businesses to begin to explore these options to reap the benefits of I4.0 is growing and while many larger organisations are maturing in their adoption many SMEs are not. This paper conducts a systematic literature review (SLR) of the tools available to organisations looking to implement I4.0. The research will focus on tools are around the areas of readiness models, maturity models and frameworks that provide detail on how to begin the journey to I4.0 implementation. The key research questions to be answered are if these tools cater to the unique needs of manufacturing SME’s and the challenges they face. What sets this SLR apart from other analysis is the identification of a research gap for a detailed framework for manufacturing SMEs to implement I4.0 in an agile and sustainable way. As the manufacturing world is changing and consumers are making more informed choices about what they buy with a view towards sustainability how can I4.0 help manufacturing SMEs operate in a sustainable way whilst remaining agile to changing economic conditions. This SLR will form the basis for further research into this area to support SMEs on their I4.0 adoption journey.

Industry 4.0 technologies enable manufacturing companies to efficiently utilise their assets and reach a competitive advantage. These technologies provide new methods of generating revenue from data-driven services and facilitate predictive maintenance through the use of real-time data analytics. Even after more than a decade from the start of the fourth industrial revolution, manufacturing industry still struggles to upgrade to Industry 4.0-compliant technologies and standards. Currently, the barriers and enablers facing manufacturing companies to adopt new technology are not well understood, and there is a significant gap in the available literature. The authors of this paper review the challenges, opportunities, and applications facing manufacturers from an academic and industrial perspective. In order to identify these factors, a literature review and a survey were chosen. Based on the results of this study, the main challenges identified are financial constraints, a lack of knowledge, and the complexity of new technologies. The research also identified opportunities for manufacturing firms, such as improving efficiency, reducing costs, and improving quality. Potential applications for manufacturers include sharing machine status, predictive maintenance and controlling machines remotely. In the current work, these factors have been ranked from an industrial perspective.

A cost-effective and accurate method to add or change sensors in an automated manufacturing line is essential in order to increase the flexibility and adaptability of production systems. In particular, small to medium enterprises (SMEs) and companies offering custom solutions can only compete in the highly interconnected age of Industry 4.0 if their operations are agile and dynamic. This paper presents a new, low-cost solution to this problem through the development of a Smart Sensor Box. The paper introduces the benefits of this highly adaptable system comparing it to currently available solutions, while testing conducted demonstrates the solution’s accuracy and repeatability. The layout and operational capabilities for three versions of the Smart Sensor Box are discussed in detail and example applications are presented.

The growing customer demand for small batch-size and customised products is putting pressure on manufacturers to adapt their current processes that were originally designed for large batch size orders. Smart manufacturing technology can be utilised to create new, effective, and sustainable processes. Many industries are still conservative when it comes to embracing smart manufacturing technologies including the textile industry. This paper demonstrates the implementation of smart technology to create a new “made to customisation” process in a textile factory. The case study involves upgrading a standard machine to a “smart” machine and utilising RFID technology to track and trace materials after they get prepared for a work order. The paper also presents a guide on how to effectively approach the implementation of smart technology in the manufacturing environment.

Artificial intelligence (AI), imitation learning, big data, cloud and distributed computing, robotics cells, and information communication technology, are some of the key tools and elements of the future digital and smart manufacturing facility. There are a number of challenges that digital and smart manufacturing is facing, especially with the complication of AI (i.e., machine, deep and cognitive learning) algorithms, great amount of data to process, and essential complex coding required, which makes immediate changes needed in manufacturing facilities not straightforward. This is notable in small manufacturing cells which is an integrated part of future smart factories such manufacturing facilities are usually needed some annual and regular updates to meet the update in the design specifications of next generation of products. Imitation learning is offering a great opportunity to overcome these challenges and simplify such complications, where human skills, ability to perform specific tasks, knowledge, and talent could be transferred. This is conveying the knowledge, and skills transfer using imitation learning. However, smart manufacturing and industrial revolution needs robotics cells that has skills beyond this, especially when it comes to process optimisation. Therefore, deep imitation learning could come in to help in the development of self-learning robotic systems and cells. Of course with the powerful tools such as distributed computing, blockchain, cloud computing, edge computing, and 5G the collaboration between such self-learning robotic cells will be possible. This will certainly not eliminate human existence but will enhance the manufacturing environment. This paper is focused on presenting the outcomes of CAD simulation and modelling phase of the ongoing research programme that focused on developing a self-learning robotic system using imitation learning. CAD tools have been used and some initial results is presented. Further work is still undertaken, and this will focus on learning from more than one expert, optimisation, impact of dynamic manufacturing environment.

Digital innovation-led industries progressively utilise different disciplinary teams to address the multidisciplinary challenges associated with highly integrated technologies. In other words, digital innovation makes businesses act rapidly in a short time frame. Creating key performance indicators to measure digital marketing and personalising and encouraging innovation in digital marketing are facilitated to adopt digital technologies. Digital and innovation go hand and hand and present a positive focus for digital transformation and innovation in line with the aims of the current market and user demand. Companies and industries operating in today’s market are experiencing many challenges, such as the globalisation of the market and technologies. From the market point of view, digital technologies permit companies to offer new digital solutions for customers based on services embedded in products. This paper proposes an innovation framework with the consideration of the so-called Industry 4.0 reflecting the current digital era requirements.

Sustaining Digital Transformation processes is a significant challenge for all organisations, especially in the manufacturing sector. Undoubtedly, Digital Transformation (DT) is becoming increasingly crucial for successfully implementing manufacturing operations. This paper discusses Digital Culture’s role in sustainable digital transformation projects by discussing the digital culture attributes that must be inside the organisation’s top management level. These attributes are collaboration, innovation, accountability, transparency, customer-centricity, and human development. By identifying these attributes in a clear and incremental model, manufacturing organisations will be able to incorporate the digital culture factor in their digital transformation operations to ensure the sustainability of these operations.

Manufacturing businesses seek to increase their revenue streams through new business models. In the context of the continuing digitization of the manufacturing sector, new business models based on digital servitization offerings are at the centre of attention. However, due to the inherent complexity involved in devising such offerings and suitable business models, many companies struggle to embark on this new value-adding pathway that is not yet well understood. Current research has highlighted the general challenges and barriers faced by manufacturing businesses, along with developing tools and roadmaps for successful transition to digital servitization. However, most studies have only focused on servitization in general, omitting the specific “digital” aspect which brings about different challenges. Accordingly, the authors first introduce the concept of digital servitization in general terms, to then discuss different types of it, along with typical barriers to entry and implementation challenges. A critical element of any digital servitization endeavor is to first assess the current state of a business, to define the desired outcome of the process, and to identify the steps and actions required to accomplish the desired end goal. This is accomplished by means of maturity models that also help in terms of benchmarking current and future state against competitors. The authors introduce the research aims and questions, the research methodology and present results from a systematic review of the literature on maturity modelling, including an overview of the maturity modelling methods encountered and their respective dimensions and levels. Finally, conclusions are drawn along with the current state of the research and future work that will be conducted.

Additive Manufacturing is rapidly developing as a cost-effective alternative to conventional manufacturing techniques for various applications requiring; components with complex geometries, introduction of sacrificial components, assemblies comprising many parts or low volume and bespoke design orders.

Cost savings can be appreciated through reduction in raw material, reduced manufacture times and removing the need for expensive tooling. Recent pandemic and Brexit highlighted supply chain instability. Delivery of replacement parts is critical for manufacturers. Downtime caused by non-productive period draws businesses and causes loss of customers. A requirement of finding solution for improved product transportation at CooperVision Manufacturing LTD, pushed for redesigning grippers used within traverse mechanism system. Redesigning would improve gripper geometry, increase grip area to subjected part and stabilize vertical and horizontal gripper position. The Additive Manufacturing Technology allows making this component from composite, making component cheaper, lighter, stronger, stiffer, and available quicker when compared to current stainless-steel components.

The aim of this paper is to assess the impacts of topology optimisation and generative design on design optimisation processes when paired with additive manufacturing. This is being done as topology optimisation is a common practice in industry, but the advent of generative design may allow for further critical refinement of parts while maintaining functionality. Additionally, when paired with additive manufacturing the benefits of generative design compound with material savings and the ability to maximise the effectiveness of generative designs complex, organic geometries. A car suspension upright was manually created as an original design. The process of topology optimisation was undertaken on the original part, and a volume reduction to the original part of 65.17% was achieved. Using a case of loading of turning braking, a generative design was produced. This achieved a volume reduction of 88.13% when compared to the original design and 65.91% when compared to the topology optimisation result. Prototype parts were then produced in ABS via the FDM additive manufacturing method as a proof of concept. The optimisation processes on the design were both successful with the topology approach providing a stronger part while the generative design provided a bespoke, refined design using much less material of organic nature. It is found that the generative methodology also provides significant positive sustainability impacts.

Lately researchers have been paying more attention to the environmental aspect, especially since our planet is nowadays threatened by multiple phenomena. In this context as a manufacturing process, the additive manufacturing appeared as a trend in its domain because it’s economic, eliminates raw material waste and allows to make complex shapes, which may not be obtained by conventional manufacturing processes. There are many additive manufacturing processes, this research will focus only on Wire Arc Additive Manufacturing which has an impact on the environment, by consuming energy (for welding, for cooling, moving the nozzle) and gases. In this paper will provide an overview to the different studies related to the environmental aspect of this process, where some have concentrated on the parameters that surround the product, other studies focused on the parameters related to the process. We will group all the ideas to find an application of the process in the context of sustainable development.

Additive manufacturing (AM) of Inconel 718, IN718, is increasingly being used for the manufacture of complex geometry parts for high temperature applications. However, the low surface integrity and build resolution of as-built AM IN718 parts demands post processing such as machining. This paper reviews the machining of AM IN718 to understand the effect of anisotropic behaviour of the AM part and the hardening post AM treatment on the machinability of the latter. A better understanding on the cutting parameters and machining performance measures such as cutting forces, tool wear, chip morphology and surface integrity of workpiece led to the development of a workplan for future investigation.

The CoRoT project is a collaboration of French and UK partners funded by the EU Interreg Programme. The CoRoT research group has developed a mobile robot demonstrating autonomous operations particularly aiming for applications within flexible manufacturing factories of small to medium enterprises (SMEs). The robot’s capability of full separation classifies it as a modular robotic system. Although the separation is possible, it introduces challenges in the areas of staff training, physical labour and workshop planning. This paper introduces a new method resolving the overt issues of lifting the robot, storing the robot and making use of the two systems as well as highlighting emergency stop regulations and maintaining the warranty of the equipment. By using a steel framed pneumatic lift, the top module can be removed and held in place, anchoring the arm for full operations whilst freeing the base to perform delivery tasks enabling seamless separation of modular robotic systems.

Co-design and co-creation of robotic systems and supporting automated solutions for industrial applications have seen a rapid increase in development efforts in recent years. Research and development activities within collaborative and industrial robotic projects alongside implementations of technical solutions have also shown significant gains in offering small, medium and some large enterprises enough cost benefit justification and improved understanding of technical requirements to adopt them in the ‘servitisation’ of manufacturing and assembly operations. This paper reports findings related to the impact of generating and exchanging technical knowledge within a large multimillion euros project in France-England Channel region over a running duration of over 5 years and the mutual benefits it had on the research institutes, industrial partners and collaborative network established from the project. The results indicated an increase in knowledge acquisition and exchange amongst individuals that can be used to gain significant advantages and a steppingstone in improving new product development activities, speed to market, as well as enhancing methods to establish long term collaborative efforts within industry-academia and improve innovation output.

Collaborative technologies can help improve work conditions for operators with any profile, in demanding production tasks. This paper presents an intervention in an intermediate stage of a Metal Injection Molding (MIM) manufacturing process with poor ergonomics, both physical and stress-related, due to sustained visual attention demands. A collaborative workstation was designed and implemented, integrating a collaborative robot and a machine-vision system for bin-picking. The strategy of the intervention was to distribute tasks between worker and robot, where the robot undertook the non-ergonomic task of arranging small pieces close together on a plate, forming a pre-established pattern. Tests with a first implementation suggest that the task-sharing intervention for the manipulation of small MIM-produced references is viable. Careful design of robot fingers is key for the manipulation of such parts, and ambiguous piece configurations require fine tuning of visual piece identification systems, for error-free execution.

Trajectory planning for robot manipulators is very important in achieving high productivity and excellent accuracy. One of the objectives nowadays is the minimum energy consumption due to the increase in the petroleum prices and the difficulty in the supply lines as well. It is the objective of this paper to design the trajectory of the manipulator based on the minimum energy consumption per cycle of the motors running the manipulator. The selected trajectory will be checked also against the jerk as well to ensure that the robot will not vibrate at the beginning and at the end of any task. A seventh-degree polynomial trajectory is selected to study the effect of the jerk on the trajectory and the torques of the joints as well. The proposed trajectory will be checked through a three degree-of-freedom robotic arm in both horizontal and vertical maneuvering.

Ceramic materials are widely used nowadays in the aerospace sector. However, functional ceramics have not yet been fully researched in terms of their life expectancy under all possible loading scenarios. Ceramics have low toughness and high brittleness, but great thermal properties as it has been widely documented in the literature. A lack of research however with regards to ceramic material life expectancy models is evident. The fatigue life of ceramic materials is not thoroughly researched and there is a need for comparing them with more traditional materials used for similar purpose applications. In the present paper, the fatigue performance of several ceramic materials will be analyzed by using S-N curves, simulating the cumulative damage caused to these materials by different constant amplitude stresses applied from a wide range of applications and more specifically, aero-engine applications. Finally, the already existing literature on ceramic failure mechanisms and models will be evaluated and compared with the simulated life expectancy models to identify improvement opportunities and a guide for developing and deploying these materials to the extended use of applications.