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This study proposes the Smart SME Technology Readiness Assessment (SSTRA) methodology which aims to enable practitioners to assess the SMEs Industry 4.0 technology readiness throughout the end-to-end engineering across the entire value chain; the smart product design phase is the focus in this paper.

The proposed SSTRA utilises the analytic hierarchy process to prioritise smart SME requirements, a graphical interface which tracks technologies' benchmarks under Industry 4.0 Technology Readiness Levels (TRLs); a mathematical model used to determine the technology readiness and visual representation to understand the relative readiness of each smart main area. The validity of the SSTRA is confirmed by testing it in a real industrial environment. In addition, the conceptual model for Smart product design development is proposed and validated.

The proposed SSTRA offers decision-makers the facility to identify requirements and rank them to reflect the current priorities of the enterprise. It allows SMEs to assess their current capabilities in a range of technologies of high relevance to the Industry 4.0 area. The SSTRA assembles a readiness profile allowing decision-makers to not only perceive the overall score of technology readiness but also the distribution of technology readiness across the main smart areas. It helps to visualise strengths and weaknesses; whilst emphasising the fundamental gaps that require serious action to assist the program with a well-balanced effort towards a successful transition to Industry 4.0.

The SSTRA provides a step-by-step approach for decision-making based on data collection, analysis, visualisation and documentation. Hence, it greatly mitigates the risk of further Industry 4.0 technology investment and implementation.

This paper aims to analyse the current state of research to identify the link between Lean Manufacturing and Industry 4.0 (I4.0) technologies to map out different research themes, to uncover research gaps and propose key recommendations for future research, including lessons to be learnt from the integration of lean and I4.0.

A systematic literature review (SLR) is conducted to thematically analyse and synthesise existing literature on Lean Manufacturing–I4.0 integration. The review analysed 60 papers in peer-reviewed journals.

In total, five main research themes were identified, and a thematic map was created to explore the following: the relationship between Lean Manufacturing and I4.0; Lean Manufacturing and I4.0 implication on performance; Lean Manufacturing and I4.0 framework; Lean Manufacturing and I4.0 integration with other methodologies; and application of I4.0 technologies in Lean Manufacturing. Furthermore, various gaps in the literature were identified, and key recommendations for future directions were proposed.

The integration of Lean Manufacturing and I4.0 will eventually bring many benefits and offers superior and long-term competitive advantages. This research reveals the need for more analysis to thoroughly examine how this can be achieved in real life and promote operational changes that ensure enterprises run more sustainably.

The development of Lean Manufacturing and I4.0 integration is still in its infancy, with most articles in this field published in the past two years. The five main research themes identified through thematic synthesis are provided in the original contribution. This provides scholars better insight into the existing literature related to Lean Manufacturing and I4.0, further contributing to defining clear topics for future research opportunities. It also has important implications for industrialists, who can develop more profound and richer knowledge than Lean and I4.0, which would, in turn, help them develop more effective deployment strategies and have a positive commercial impact.

The paper seeks to report on some of the preliminary results of an ongoing scoping study into the shape of the manufacturing enterprise of the future.

This paper evolved through a combination of literature review, focused group discussions, interviews and a questionnaire survey of six aerospace companies in the UK. It is primarily an attempt to provide a broad framework for synthesizing some of the information generally available as a contribution to the current debate regarding the future of manufacturing systems.

The results to date show that the product development process and supply network efficiency are the two most significant domains influencing manufacturing responsiveness. Within those domains, customer driven product development and supply chain design, intelligent and flexible technology, producibility analysis, integrated product and process development and the concurrency of the extended manufacturing enterprise are considered as the most significant elements towards achieving responsiveness. In addition a Responsive Manufacturing Model (RMM) is provided.

The RMM reported in the paper is at an early state of development and the work is ongoing to refine it further. The development of appropriate measures and methods of assessment for the various facets and attributes of manufacturing responsiveness is an important step towards full model development which is still to be addressed.

The process of structuring the various elements influencing manufacturing responsiveness into logical groups in a hierarchical model has proved very useful during model development. It proved a significant aid during the focused group discussions and interviews that preceded completion of the questionnaire. The results to date are very encouraging and provide several interesting insights into the domains and elements of manufacturing responsiveness and the relative importance attached to them in the UK aerospace sector.

The work was funded by EPSRC (IMI) research grant as it was the first attempt in this field over within the UK. The proposed model and the obtained results have led to another research project funded by EPSRC over three years to further investigate the proposed model and the implication of its implementation.

In this paper manufacturing responsiveness is related to the ability of manufacturing systems to utilise its existing resources to make a rapid and balanced response to the predictable and unpredictable changes. Better understanding of the inherent (hidden) flexibility that exists within a manufacturing system can therefore lead to significant improvement in system performance and responsiveness. In the reported research a conceptual framework for representing the capabilities of machine tools and machining facilities using generic capabilities units termed “resource elements” is presented as well as a mathematical basis of calculating the manufacturing system flexibility using the resource elements. Simulations are used to examine manufacturing system performance and compare resource element‐based scheduling with conventional machine‐based approaches. The results show that significant improvements in system performance and the system’s ability to cope with disturbances can be achieved if manufacturing facilities are represented and scheduled based on the resource elements concept.

The purpose of this paper is to develop an integrated‐cost optimization maintenance model for industrial equipment, based on a balance between preventive and corrective maintenance costs.

The proposed model is mathematically based and takes into consideration the stochastic nature of equipment failures. The output from the model is a cost distribution against time from which the minimum cost may be found for a particular period and this period is defined as the optimum lifespan of the machine part.

The output from the proposed model was constrained to the production conditions on machine level. This constrained output was then refined subject to recent failure trends in comparison with historical trends. Guidelines have also been given for a smooth completion of the maintenance actions on a machining cell level. The anticipation of the failure rate of every machine‐part is made possible as well as the improvement of the part's availability at an extra financial cost that would be clearly anticipated. The results promise improvement in equipment availability, inventory and workforce planning, along with reductions in failure rates.

The implementation of the proposed model is expected to have a significant impact on an industrial organisation in terms of reducing its maintenance‐related costs, production lines backlogs and scrap rates.

The angle, from which the paper approaches the maintenance problem in industry, is original in nature and beneficial in result. It allows the user to have a deep understanding of his/her industrial domain without being involved in too much theoretical derivation. It also helps the user to treat only the contaminated spot (machine‐part) and not the whole assembly (the machine), which adds accuracy and potential impact to the output.

A comprehensive analysis of a flexible hybrid assembly system (FHAS) where automated devices and human operators interact is presented. A computer simulation programme and ANOVA were conducted to identify which factors significantly affect the measures of performance of the system. The results clearly indicated that certain factors have a more significant effect on the measures of performance than the others. A classification of the relative significance of input factors affecting such a system is made. In order to investigate the generality of the results, alternative station configurations and factor levels are examined. The outcome shows that the results are applicable to different configurations of FHAS.

In this paper, an integrated model for order release and due‐date management is developed to enhance manufacturers’ confidence in the due‐dates offered to customers. The proposed model utilised the backward finite scheduling order release control method and five different due‐date assignment rules. The proposed model is implemented using C++ computer programming language. Due‐date of each order is calculated by a due‐date assignment rule selected. Then the program tries to schedule the whole order with as lowest value as possible of tightness parameter (k). The output of the C++ program is production schedule of the whole order using backward finite scheduling order release method. Experiment results indicate that the modified number of operations due‐date rule_MNOP is superior with respect to the other due‐dates rules of the whole order.

To highlight the differences and common features of taboo search (TS) and genetic algorithms (GA) in solving the problem of board‐type sequencing on the assembly line simultaneously with the combined problem of feeder assignment and component placement sequencing in the printed circuit board (PCB) industry.

Two metaheuristics (search techniques) are used to solve three problems associated with the PCB assembly line: TS and GA. The implemented approach is used to solve the three problems on a single pick‐and‐place sequential machine with a stationary board table and stationary feeders, and with the use of the Euclidean metric.

The achieved results show a satisfactory reduction in assembly time, when TS and GA are compared with a random solution, with a slight superiority of TS over GA. However, the program running time is longer for TS.

The hypothetical case study used shows that in real life the savings could reach an average of 6 per cent when TS is used. Slightly lower savings are possible when GA is used.

This paper provides a clear insight into how some of the problems associated with the production of PCBs can be solved simultaneously using metaheuristics such as TS and GA.