Skip to main content

Yuchun Xu

Aston University, College of Engineering and Physical Sciences, Faculty Member

Followers

9

Following

1

Public Views

Professor Yuchun Xu is the Chair in Manufacturing, Director of Smart and Sustainable Manufacturing Research Centre (SMRC) at Aston University, United Kingdom. His research lies in the areas of Smart Manufacturing, Remanufacturing, Life Cycle Engineering and Circular Economy. Prof Xu’s research is sponsored by EPSRC, Innovate UK and Horizon EU/2000, and EU FP7 etc. His research is primarily focused on developing digital solutions to address sustainability challenges and facilitating the digital and green transition of industry and society. His research spans full product life cycle, including design, development, manufacturing, maintenance, remanufacturing/life extension, and recycle/disposal.

less

Hatim Aboalsamh

King Saud University

Fraunhofer

Jaroslava Kádárová

Mukti Chaturvedi

Hassan M. H. Farh

King Saud University

Interests

Uploads

Papers by Yuchun Xu

Multi-Objective Considered Process Parameter Optimization of Welding Robots Based on Small Sample Size Dataset

Sustainability

The welding process is characterized by its high energy density, making it imperative to optimize... more The welding process is characterized by its high energy density, making it imperative to optimize the energy consumption of welding robots without compromising the quality and efficiency of the welding process for their sustainable development. The above evaluation objectives in a particular welding situation are mostly influenced by the welding process parameters. Although numerical analysis and simulation methods have demonstrated their viability in optimizing process parameters, there are still limitations in terms of modeling accuracy and efficiency. This paper presented a framework for optimizing process parameters of welding robots in industry settings, where data augmentation was applied to expand sample size, auto machine learning theory was incorporated to quantify reflections from process parameters to evaluation objectives, and the enhanced non-dominated sorting algorithm was employed to identify an optimal solution by balancing these objectives. Additionally, an experime...

Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing

Circular Economy and Sustainability

Industrial equipment/machinery is an important element of manufacturing. They are used for produc... more Industrial equipment/machinery is an important element of manufacturing. They are used for producing objects that people need for everyday use. Therefore, there is a challenge to adopt effective maintenance strategies to keep them well-functioning and well-maintained in production lines. This will save energy and materials and contribute genuinely to the circular economy and creating value. Remanufacturing or refurbishment is one of the strategies to extend life of such industrial equipment. The paper presents an initial framework of cost estimation model based on combination of activity-based costing (ABC) and human expertise to assist the decision-making on best life extension strategy (e.g. remanufacturing, refurbishment, repair) for industrial equipment. Firstly, ABC cost model is developed to calculate cost of life extension strategy to be used as a benchmark strategy. Next, expert opinions are employed to modify data of benchmark strategy, which is then used to estimate costs ...

A Distributional Perspective on Remaining Useful Life Prediction With Deep Learning and Quantile Regression

IEEE Open Journal of Instrumentation and Measurement

With the rapid development of information and sensor technology, the data-driven remaining useful... more With the rapid development of information and sensor technology, the data-driven remaining useful lifetime (RUL) prediction methods have been acquired a successful development. Nowadays, the data-driven RUL methods are focused on estimating the RUL value. However, it is more important to quantify the uncertainty associated with the RUL value. This is because increasingly complex industrial systems would arise various sources of uncertainty. This article proposes a novel distributional RUL prediction method, which aims at quantifying the RUL uncertainty by identifying the confidence interval with the cumulative distribution function (CDF). The proposed learning method has been built based on quantile regression and implemented from a distributional perspective under the deep neural network framework. The results of the run-to-failure degradation experiments of rolling bearing demonstrate the effectiveness and good performance of the proposed method compared to other state-of-the-art methods. The visualization results obtained by t-SNE technology have been investigated to further verify the effectiveness and generalization ability of the proposed method. INDEX TERMS Deep learning, distributional remaining useful lifetime (RUL) prediction, quantile regression, rolling bearing, uncertainty.

Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization

Sustainability

With the rapid development of Industrial 4.0, the modern manufacturing system has been experienci... more With the rapid development of Industrial 4.0, the modern manufacturing system has been experiencing profoundly digital transformation. The development of new technologies helps to improve the efficiency of production and the quality of products. However, for the increasingly complex production systems, operational decision making encounters more challenges in terms of having sustainable manufacturing to satisfy customers and markets’ rapidly changing demands. Nowadays, rule-based heuristic approaches are widely used for scheduling management in production systems, which, however, significantly depends on the expert domain knowledge. In this way, the efficiency of decision making could not be guaranteed nor meet the dynamic scheduling requirement in the job-shop manufacturing environment. In this study, we propose using deep reinforcement learning (DRL) methods to tackle the dynamic scheduling problem in the job-shop manufacturing system with unexpected machine failure. The proximal ...

Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction

Applied Sciences, 2022

Remanufacturing is an activity of the circular economy model whose purpose is to keep the high va... more Remanufacturing is an activity of the circular economy model whose purpose is to keep the high value of products and materials. As opposed to the currently employed linear economic model, remanufacturing targets the extension of products and reduces the unnecessary and wasteful use of resources. Remanufacturing, along with health status monitoring, constitutes a key element for lifetime extension and reuse of large industrial equipment. The major challenge is to determine if a machine is worth remanufacturing and when is the optimal time to perform remanufacturing. The present work proposes a new predictive maintenance framework for the remanufacturing process based on a combination of remaining useful life prediction and condition monitoring methods. A hybrid-driven approach was used to combine the advantages of the knowledge model and historical data. The proposed method has been verified on the realistic run-to-failure rolling bearing degradation dataset. The experimental results...

RECLAIM: Toward a New Era of Refurbishment and Remanufacturing of Industrial Equipment

Frontiers in Artificial Intelligence, 2021

Refurbishment and remanufacturing are the industrial processes whereby used products or parts tha... more Refurbishment and remanufacturing are the industrial processes whereby used products or parts that constitute the product are restored. Remanufacturing is the process of restoring the functionality of the product or a part of it to “as-new” quality, whereas refurbishment is the process of restoring the product itself or part of it to “like-new” quality, without being as thorough as remanufacturing. Within this context, the EU-funded project RECLAIM presents a new idea on refurbishment and remanufacturing based on big data analytics, machine learning, predictive analytics, and optimization models using deep learning techniques and digital twin models with the aim of enabling the stakeholders to make informed decisions about whether to remanufacture, upgrade, or repair heavy machinery that is toward its end-of-life. The RECLAIM project additionally provides novel strategies and technologies that enable the reuse of industrial equipment in old, renewed, and new factories, with the goal...

Cost-Efficient Materials in Aerospace: Composite vs Aluminium

Collaborative Product and Service Life Cycle Management for a Sustainable World

Aluminium alloys are a series of traditional materials applied in aerospace industry. Composite m... more Aluminium alloys are a series of traditional materials applied in aerospace industry. Composite materials have been being used to replace some aluminium alloys in airframe structures. To select a cost-efficient material in aerospace design, a framework for systematic assessment of composites and aluminium is therefore suggested. Through evaluation of 3Ps which represent prices, properties and processing of material, life cycle assessment of aluminium and composite could be made. By comparison of and trade-off the listed baselines of 3Ps, an economic, rational, available and useful material can be logically selected.

Development of a validation and qualification process for the manufacturing of medical devices: a case study based on cross-sector benchmarking

International Journal of Process Management and Benchmarking, 2018

The validation stage plays a critical role in the development and production of medical devices; ... more The validation stage plays a critical role in the development and production of medical devices; it ensures new medical devices meet all the functional, reliability and quality requirements of both customer and regulatory authorities. This paper presents a case study concerning validation and qualification process for medical devices in a UK-based medical device manufacturer. The work aims to develop an efficient and highly reliable procedure for the validation of medical devices. A benchmarking study has been performed to identify the best practices in product validation. The existing practices within the case study manufacturer have been reviewed to identify opportunities for validation improvement. New practices have been proposed for the case study manufacturer, and guidelines for implementing the proposed validation procedures have also been developed.

State of the art of information systems failure managements

Information systems (IS) play a vital role in our daily life. They collect, store, organize and d... more Information systems (IS) play a vital role in our daily life. They collect, store, organize and distribute data in structured and organized ways to improve people's daily activities in the most efficient and effective manner. To achieve that, functions and structures are mixed together in a dynamic way to construct an information system with sophisticated capabilities beyond sending emails and publishing data online. Consequently, enterprises and government departments allocate huge financial and human resources for the development of interconnected information systems. However, failures in information systems projects have been growing in the last few years despite their massive allocated resources. That means any IS projects that do not meet their objectives and goal have gone beyond budget or not completed within the agreed time. While there are several factors triggering these failures, this research aims to investigate and address the key factors that are responsible for fa...

Lean Six Sigma(LSS) practices of supply chain

The aim of this paper is highlight lean six sigma (LSS) practices of supply chain by reviewing ex... more The aim of this paper is highlight lean six sigma (LSS) practices of supply chain by reviewing extant literature. A key words literature review approach is adopted to generate a list of possible LSS factors (practices) in different sectors with focus on healthcare sector. As a result, the most frequently practices have been extracted.

Abstracts III International Workshop on Autononomous Remanufacturing Book of Abstracts III International Workshop on Autonomous Remanufacturing

S III INTERNATIONAL WORKSHOP ON AUTONONOMOUS REMANUFACTURING

Ergonomic evaluation on the manufacturing shop floor: A review of hardware and software technologies

CIRP Journal of Manufacturing Science and Technology, 2020

The high rate of work-related musculoskeletal disorders (WMSDs) among workers on the shop floor h... more The high rate of work-related musculoskeletal disorders (WMSDs) among workers on the shop floor has led to the development of various ergonomic evaluation and risk assessment tools by researchers. This paper presents a summary of existing literature reviews of hardware and software technologies developed for effective ergonomic evaluation and correct risk assessment on manufacturing shop floors. Criteria was set for the review and after comprehensive search on 14 databases, 24 studies met the criteria. Old and modern ergonomic evaluation hardware and software technologies for effective evaluation on shop floors are identified. Most literatures cited the digital human models (DHMs), which can be created on many ergonomic evaluation software tools, to be an effective ergonomic evaluation tool. Gaps are identified with the use of DHMs for ergonomic evaluations. Ultimately, this study is a contribution towards identifying adequate ergonomic evaluation and correct risk assessment tools which when implemented on the Shop floor, can lead to improved productivity, enhanced efficiency and reduced cost.

Towards Smart Remanufacturing and Maintenance of Machinery - Review of Automated Inspection, Condition Monitoring and Production Optimisation

2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020

Modern manufacturing has made huge progress in production efficiency. However, the status of the ... more Modern manufacturing has made huge progress in production efficiency. However, the status of the production equipment deteriorates during manufacturing, and their condition can then affect the quality of products and total production cost. When viable, maintenance, remanufacturing and replacement should be carried out for such equipment to reduce the total production cost. However, many processes, for example, inspection and manufacturing planning are carried out by a human. In the era of Industry 4.0, an automated production planning with automated condition monitoring, equipment inspection and maintenance planning is desired. In this article, the literature on related topics is reviewed. The state of the art in this study helps to improve the performance of production lines in manufacturing.

The aperiodic facility layout problem with time-varying demands and an optimal master-slave solution approach

International Journal of Production Research, 2020

In many seasonal industries, market demands are constantly changing over time and accordingly the... more In many seasonal industries, market demands are constantly changing over time and accordingly the facility layout should be re-optimized timely in order to adapt to the expected material handling patterns between manufacturing departments. This paper investigated the aperiodic facility layout problem (AFLP) that involves arranging facilities layout and re-layout aperiodically in a given planning horizon in a dynamic manufacturing environment. The AFLP is decomposed into a master problem and a slave problem without loss of optimality in this paper, and all problems are formulated as mixed-integer linear programming (MILP) models that are directly solvable to MIP solvers for small-sized problems. An exact backward dynamic programming (BDP) algorithm is developed for the master problem of large-size with a computational complexity level of O(n 2), and an improved version of problem evolution algorithm based on linear programming (PEA-LP) is developed for the slave problem of all sizes. Computational experiments are conducted on two new provisioned problems and twelve benchmarked problems in literature, and the experimental results show that the proposed solution approach is promising for solving the AFLP with all sizes of problem instances, where five benchmark problems have found new best solutions by using the improved PEA-LP algorithm.

A new formulation of the electric vehicle routing problem with time windows considering concave nonlinear charging function

Journal of Cleaner Production, 2019

The electric vehicle routing problem with time window (EVRPTW) is an extension of the traditional... more The electric vehicle routing problem with time window (EVRPTW) is an extension of the traditional vehicle routing problem with time window (VRPTWs), where new features of electric vehicles are considered, such as limited battery capacities, lack of infrastructures, and long charging time. In this study, new technical formulations were presented for vehicle route selection and charging station visit, which reduces the formulation complexity without using duplicated dummy nodes or arcs. Besides, a new linearization method was developed that employs a set of secant lines to surrogate the concave nonlinear charging function with linear constraints. This method defines the charging time as a continuous variable and uses fewer variables than existing formulation in literature. A mixedinteger linear programming (MILP) model was developed for the EVRPTW and computational experiments on Solomon's VRPTW instances were conducted to verify the proposed model. The experimental results were compared with the results using traditional routing models, which showed that the proposed model can result in better EVs logistics schedules with higher charging time utilizations. One benchmark problem was updated with new best solution.

Design and implementation of ergonomic risk assessment feedback system for improved work posture assessment

Theoretical Issues in Ergonomics Science, 2017

Ergonomic risk factors which include force, repetition and awkward postures, can result in Work-R... more Ergonomic risk factors which include force, repetition and awkward postures, can result in Work-Related Musculoskeletal Disorders (WMSDs) among workers. Hence, systems that provide real-time feedback to the worker concerning his current ergonomic behaviours are desirable. This paper presents the design and implementation of a human-machine interface posture assessment feedback system whose conceptual model is developed through a model-driven development perspective using the UML and Interface flow diagrams. The resulting system provides a shop floor with a simple, cost-effective and automatic tool for real-time display of worker's postures. Testing the system on volunteer participants reveals that it is easy to use, achieves real-time posture assessment and provides easy-tounderstand feedback to workers. This system may be useful for reducing the rate of occurrence of awkward postures, one of the contributing factors to risk of WMSDs among workers.

An Internet of Things based framework to enhance just-in-time manufacturing

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2017

Just-in-time manufacturing is a main manufacturing strategy used to enhance manufacturers’ compet... more Just-in-time manufacturing is a main manufacturing strategy used to enhance manufacturers’ competitiveness through inventory and lead time reduction. Implementing just-in-time manufacturing has a number of challenges, for example, effective, frequent and real-time information sharing and communication between different functional departments, responsive action for adjusting the production plan against the continually changing manufacturing situation. Internet of Things technology has the potential to be used for capturing desired data and information from production environment in real time, and the collected data and information can be used for adjusting production schedules corresponding to the changing production environment. This article presents an Internet of Things based framework to support responsive production planning and scheduling in just-in-time manufacturing. The challenges of implementing just-in-time manufacturing are identified first and then an Internet of Things ...

An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost

Transportation Research Part C: Emerging Technologies, 2018

National railways are typically large and complex systems. Their network infrastructure usually i... more National railways are typically large and complex systems. Their network infrastructure usually includes extended track sections, bridges, stations and other supporting assets. In recent years, railways have also become a data-rich environment. Railway infrastructure assets have a very long life, but inherently degrade. Interventions are necessary but they can cause lateness, damage and hazards. Every day, thousands of discrete maintenance jobs are scheduled according to time and urgency. Service disruption has a direct economic impact. Planning for maintenance can be complex, expensive and uncertain. Autonomous scheduling of maintenance jobs is essential. The design strategy of a novel integrated system for automatic job scheduling is presented; from concept formulation to the examination of the data to information transitional level interface, and at the decision making level. The underlying architecture configures high-level fusion of technical and business drivers; scheduling optimized intervention plans that factor-in cost impact and added value. A proof of concept demonstrator was developed to validate the system principle and to test algorithm functionality. It employs a dashboard for visualization of the system response and to present key information. Real track incident and inspection datasets were analyzed to raise degradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum scheduling was realized through data analytics and job sequencing heuristic and genetic algorithms, taking into account specific cost & value inputs from comprehensive task cost modelling. Formal face validation was conducted with railway infrastructure specialists and stakeholders. The demonstrator structure was found fit for purpose with logical component relationships, offering further scope for research and commercial exploitation.

The Role of Leadership in Implementing Lean Manufacturing

Procedia CIRP, 2017

It is widely accepted that for the successful implementation of lean manufacturing, the senior ma... more It is widely accepted that for the successful implementation of lean manufacturing, the senior management commitment is of great importance. However, the lean journey is usually a long one, and eventually management commitment creeps. Furthermore, the involvement of employees in daily improvements is also critical for the success of implementation. Lean leadership can be considered as a way of sustaining and improving the employee performance in lean production systems. In the present study, a thorough literature review is presented focusing in reviewing the principles of lean leadership and the practices that can lead in improving the employee performance. Furthermore, the characteristics and qualities of lean leader are discussed.

Lean Implementation Frameworks: The Challenges for SMEs

Procedia CIRP, 2017

Implementation of lean manufacturing in any type of organizations can bring many benefits, such a... more Implementation of lean manufacturing in any type of organizations can bring many benefits, such as reducing waste and improving operating efficiency. However, lean implementation is not a straightforward process. Although a number of frameworks have been presented, still many companies find it difficult to implement lean. Furthermore, most of these roadmaps are for large manufacturing companies, and not for small and medium enterprises. Unfortunately, there is not a recipe that if used can guarantee a successful implementation. Furthermore, unsuccessful implementation can have a great impact on organization's resources, but even more importantly, affect employees and their confidence in lean philosophy. In the present paper, the most prominent lean implementation frameworks will be discussed, under the prism of the needs of SMEs. The challenges for the SMEs in their lean journey are discussed.

Multi-Objective Considered Process Parameter Optimization of Welding Robots Based on Small Sample Size Dataset

Sustainability

The welding process is characterized by its high energy density, making it imperative to optimize... more The welding process is characterized by its high energy density, making it imperative to optimize the energy consumption of welding robots without compromising the quality and efficiency of the welding process for their sustainable development. The above evaluation objectives in a particular welding situation are mostly influenced by the welding process parameters. Although numerical analysis and simulation methods have demonstrated their viability in optimizing process parameters, there are still limitations in terms of modeling accuracy and efficiency. This paper presented a framework for optimizing process parameters of welding robots in industry settings, where data augmentation was applied to expand sample size, auto machine learning theory was incorporated to quantify reflections from process parameters to evaluation objectives, and the enhanced non-dominated sorting algorithm was employed to identify an optimal solution by balancing these objectives. Additionally, an experime...

Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing

Circular Economy and Sustainability

Industrial equipment/machinery is an important element of manufacturing. They are used for produc... more Industrial equipment/machinery is an important element of manufacturing. They are used for producing objects that people need for everyday use. Therefore, there is a challenge to adopt effective maintenance strategies to keep them well-functioning and well-maintained in production lines. This will save energy and materials and contribute genuinely to the circular economy and creating value. Remanufacturing or refurbishment is one of the strategies to extend life of such industrial equipment. The paper presents an initial framework of cost estimation model based on combination of activity-based costing (ABC) and human expertise to assist the decision-making on best life extension strategy (e.g. remanufacturing, refurbishment, repair) for industrial equipment. Firstly, ABC cost model is developed to calculate cost of life extension strategy to be used as a benchmark strategy. Next, expert opinions are employed to modify data of benchmark strategy, which is then used to estimate costs ...

A Distributional Perspective on Remaining Useful Life Prediction With Deep Learning and Quantile Regression

IEEE Open Journal of Instrumentation and Measurement

With the rapid development of information and sensor technology, the data-driven remaining useful... more With the rapid development of information and sensor technology, the data-driven remaining useful lifetime (RUL) prediction methods have been acquired a successful development. Nowadays, the data-driven RUL methods are focused on estimating the RUL value. However, it is more important to quantify the uncertainty associated with the RUL value. This is because increasingly complex industrial systems would arise various sources of uncertainty. This article proposes a novel distributional RUL prediction method, which aims at quantifying the RUL uncertainty by identifying the confidence interval with the cumulative distribution function (CDF). The proposed learning method has been built based on quantile regression and implemented from a distributional perspective under the deep neural network framework. The results of the run-to-failure degradation experiments of rolling bearing demonstrate the effectiveness and good performance of the proposed method compared to other state-of-the-art methods. The visualization results obtained by t-SNE technology have been investigated to further verify the effectiveness and generalization ability of the proposed method. INDEX TERMS Deep learning, distributional remaining useful lifetime (RUL) prediction, quantile regression, rolling bearing, uncertainty.

Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization

Sustainability

With the rapid development of Industrial 4.0, the modern manufacturing system has been experienci... more With the rapid development of Industrial 4.0, the modern manufacturing system has been experiencing profoundly digital transformation. The development of new technologies helps to improve the efficiency of production and the quality of products. However, for the increasingly complex production systems, operational decision making encounters more challenges in terms of having sustainable manufacturing to satisfy customers and markets’ rapidly changing demands. Nowadays, rule-based heuristic approaches are widely used for scheduling management in production systems, which, however, significantly depends on the expert domain knowledge. In this way, the efficiency of decision making could not be guaranteed nor meet the dynamic scheduling requirement in the job-shop manufacturing environment. In this study, we propose using deep reinforcement learning (DRL) methods to tackle the dynamic scheduling problem in the job-shop manufacturing system with unexpected machine failure. The proximal ...

Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction

Applied Sciences, 2022

Remanufacturing is an activity of the circular economy model whose purpose is to keep the high va... more Remanufacturing is an activity of the circular economy model whose purpose is to keep the high value of products and materials. As opposed to the currently employed linear economic model, remanufacturing targets the extension of products and reduces the unnecessary and wasteful use of resources. Remanufacturing, along with health status monitoring, constitutes a key element for lifetime extension and reuse of large industrial equipment. The major challenge is to determine if a machine is worth remanufacturing and when is the optimal time to perform remanufacturing. The present work proposes a new predictive maintenance framework for the remanufacturing process based on a combination of remaining useful life prediction and condition monitoring methods. A hybrid-driven approach was used to combine the advantages of the knowledge model and historical data. The proposed method has been verified on the realistic run-to-failure rolling bearing degradation dataset. The experimental results...

RECLAIM: Toward a New Era of Refurbishment and Remanufacturing of Industrial Equipment

Frontiers in Artificial Intelligence, 2021

Refurbishment and remanufacturing are the industrial processes whereby used products or parts tha... more Refurbishment and remanufacturing are the industrial processes whereby used products or parts that constitute the product are restored. Remanufacturing is the process of restoring the functionality of the product or a part of it to “as-new” quality, whereas refurbishment is the process of restoring the product itself or part of it to “like-new” quality, without being as thorough as remanufacturing. Within this context, the EU-funded project RECLAIM presents a new idea on refurbishment and remanufacturing based on big data analytics, machine learning, predictive analytics, and optimization models using deep learning techniques and digital twin models with the aim of enabling the stakeholders to make informed decisions about whether to remanufacture, upgrade, or repair heavy machinery that is toward its end-of-life. The RECLAIM project additionally provides novel strategies and technologies that enable the reuse of industrial equipment in old, renewed, and new factories, with the goal...

Cost-Efficient Materials in Aerospace: Composite vs Aluminium

Collaborative Product and Service Life Cycle Management for a Sustainable World

Aluminium alloys are a series of traditional materials applied in aerospace industry. Composite m... more Aluminium alloys are a series of traditional materials applied in aerospace industry. Composite materials have been being used to replace some aluminium alloys in airframe structures. To select a cost-efficient material in aerospace design, a framework for systematic assessment of composites and aluminium is therefore suggested. Through evaluation of 3Ps which represent prices, properties and processing of material, life cycle assessment of aluminium and composite could be made. By comparison of and trade-off the listed baselines of 3Ps, an economic, rational, available and useful material can be logically selected.

Development of a validation and qualification process for the manufacturing of medical devices: a case study based on cross-sector benchmarking

International Journal of Process Management and Benchmarking, 2018

The validation stage plays a critical role in the development and production of medical devices; ... more The validation stage plays a critical role in the development and production of medical devices; it ensures new medical devices meet all the functional, reliability and quality requirements of both customer and regulatory authorities. This paper presents a case study concerning validation and qualification process for medical devices in a UK-based medical device manufacturer. The work aims to develop an efficient and highly reliable procedure for the validation of medical devices. A benchmarking study has been performed to identify the best practices in product validation. The existing practices within the case study manufacturer have been reviewed to identify opportunities for validation improvement. New practices have been proposed for the case study manufacturer, and guidelines for implementing the proposed validation procedures have also been developed.

State of the art of information systems failure managements

Information systems (IS) play a vital role in our daily life. They collect, store, organize and d... more Information systems (IS) play a vital role in our daily life. They collect, store, organize and distribute data in structured and organized ways to improve people's daily activities in the most efficient and effective manner. To achieve that, functions and structures are mixed together in a dynamic way to construct an information system with sophisticated capabilities beyond sending emails and publishing data online. Consequently, enterprises and government departments allocate huge financial and human resources for the development of interconnected information systems. However, failures in information systems projects have been growing in the last few years despite their massive allocated resources. That means any IS projects that do not meet their objectives and goal have gone beyond budget or not completed within the agreed time. While there are several factors triggering these failures, this research aims to investigate and address the key factors that are responsible for fa...

Lean Six Sigma(LSS) practices of supply chain

The aim of this paper is highlight lean six sigma (LSS) practices of supply chain by reviewing ex... more The aim of this paper is highlight lean six sigma (LSS) practices of supply chain by reviewing extant literature. A key words literature review approach is adopted to generate a list of possible LSS factors (practices) in different sectors with focus on healthcare sector. As a result, the most frequently practices have been extracted.

Abstracts III International Workshop on Autononomous Remanufacturing Book of Abstracts III International Workshop on Autonomous Remanufacturing

S III INTERNATIONAL WORKSHOP ON AUTONONOMOUS REMANUFACTURING

Ergonomic evaluation on the manufacturing shop floor: A review of hardware and software technologies

CIRP Journal of Manufacturing Science and Technology, 2020

The high rate of work-related musculoskeletal disorders (WMSDs) among workers on the shop floor h... more The high rate of work-related musculoskeletal disorders (WMSDs) among workers on the shop floor has led to the development of various ergonomic evaluation and risk assessment tools by researchers. This paper presents a summary of existing literature reviews of hardware and software technologies developed for effective ergonomic evaluation and correct risk assessment on manufacturing shop floors. Criteria was set for the review and after comprehensive search on 14 databases, 24 studies met the criteria. Old and modern ergonomic evaluation hardware and software technologies for effective evaluation on shop floors are identified. Most literatures cited the digital human models (DHMs), which can be created on many ergonomic evaluation software tools, to be an effective ergonomic evaluation tool. Gaps are identified with the use of DHMs for ergonomic evaluations. Ultimately, this study is a contribution towards identifying adequate ergonomic evaluation and correct risk assessment tools which when implemented on the Shop floor, can lead to improved productivity, enhanced efficiency and reduced cost.

Towards Smart Remanufacturing and Maintenance of Machinery - Review of Automated Inspection, Condition Monitoring and Production Optimisation

2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020

Modern manufacturing has made huge progress in production efficiency. However, the status of the ... more Modern manufacturing has made huge progress in production efficiency. However, the status of the production equipment deteriorates during manufacturing, and their condition can then affect the quality of products and total production cost. When viable, maintenance, remanufacturing and replacement should be carried out for such equipment to reduce the total production cost. However, many processes, for example, inspection and manufacturing planning are carried out by a human. In the era of Industry 4.0, an automated production planning with automated condition monitoring, equipment inspection and maintenance planning is desired. In this article, the literature on related topics is reviewed. The state of the art in this study helps to improve the performance of production lines in manufacturing.

The aperiodic facility layout problem with time-varying demands and an optimal master-slave solution approach

International Journal of Production Research, 2020

In many seasonal industries, market demands are constantly changing over time and accordingly the... more In many seasonal industries, market demands are constantly changing over time and accordingly the facility layout should be re-optimized timely in order to adapt to the expected material handling patterns between manufacturing departments. This paper investigated the aperiodic facility layout problem (AFLP) that involves arranging facilities layout and re-layout aperiodically in a given planning horizon in a dynamic manufacturing environment. The AFLP is decomposed into a master problem and a slave problem without loss of optimality in this paper, and all problems are formulated as mixed-integer linear programming (MILP) models that are directly solvable to MIP solvers for small-sized problems. An exact backward dynamic programming (BDP) algorithm is developed for the master problem of large-size with a computational complexity level of O(n 2), and an improved version of problem evolution algorithm based on linear programming (PEA-LP) is developed for the slave problem of all sizes. Computational experiments are conducted on two new provisioned problems and twelve benchmarked problems in literature, and the experimental results show that the proposed solution approach is promising for solving the AFLP with all sizes of problem instances, where five benchmark problems have found new best solutions by using the improved PEA-LP algorithm.

A new formulation of the electric vehicle routing problem with time windows considering concave nonlinear charging function

Journal of Cleaner Production, 2019

The electric vehicle routing problem with time window (EVRPTW) is an extension of the traditional... more The electric vehicle routing problem with time window (EVRPTW) is an extension of the traditional vehicle routing problem with time window (VRPTWs), where new features of electric vehicles are considered, such as limited battery capacities, lack of infrastructures, and long charging time. In this study, new technical formulations were presented for vehicle route selection and charging station visit, which reduces the formulation complexity without using duplicated dummy nodes or arcs. Besides, a new linearization method was developed that employs a set of secant lines to surrogate the concave nonlinear charging function with linear constraints. This method defines the charging time as a continuous variable and uses fewer variables than existing formulation in literature. A mixedinteger linear programming (MILP) model was developed for the EVRPTW and computational experiments on Solomon's VRPTW instances were conducted to verify the proposed model. The experimental results were compared with the results using traditional routing models, which showed that the proposed model can result in better EVs logistics schedules with higher charging time utilizations. One benchmark problem was updated with new best solution.

Design and implementation of ergonomic risk assessment feedback system for improved work posture assessment

Theoretical Issues in Ergonomics Science, 2017

Ergonomic risk factors which include force, repetition and awkward postures, can result in Work-R... more Ergonomic risk factors which include force, repetition and awkward postures, can result in Work-Related Musculoskeletal Disorders (WMSDs) among workers. Hence, systems that provide real-time feedback to the worker concerning his current ergonomic behaviours are desirable. This paper presents the design and implementation of a human-machine interface posture assessment feedback system whose conceptual model is developed through a model-driven development perspective using the UML and Interface flow diagrams. The resulting system provides a shop floor with a simple, cost-effective and automatic tool for real-time display of worker's postures. Testing the system on volunteer participants reveals that it is easy to use, achieves real-time posture assessment and provides easy-tounderstand feedback to workers. This system may be useful for reducing the rate of occurrence of awkward postures, one of the contributing factors to risk of WMSDs among workers.

An Internet of Things based framework to enhance just-in-time manufacturing

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2017

Just-in-time manufacturing is a main manufacturing strategy used to enhance manufacturers’ compet... more Just-in-time manufacturing is a main manufacturing strategy used to enhance manufacturers’ competitiveness through inventory and lead time reduction. Implementing just-in-time manufacturing has a number of challenges, for example, effective, frequent and real-time information sharing and communication between different functional departments, responsive action for adjusting the production plan against the continually changing manufacturing situation. Internet of Things technology has the potential to be used for capturing desired data and information from production environment in real time, and the collected data and information can be used for adjusting production schedules corresponding to the changing production environment. This article presents an Internet of Things based framework to support responsive production planning and scheduling in just-in-time manufacturing. The challenges of implementing just-in-time manufacturing are identified first and then an Internet of Things ...

An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition, planning and cost

Transportation Research Part C: Emerging Technologies, 2018

National railways are typically large and complex systems. Their network infrastructure usually i... more National railways are typically large and complex systems. Their network infrastructure usually includes extended track sections, bridges, stations and other supporting assets. In recent years, railways have also become a data-rich environment. Railway infrastructure assets have a very long life, but inherently degrade. Interventions are necessary but they can cause lateness, damage and hazards. Every day, thousands of discrete maintenance jobs are scheduled according to time and urgency. Service disruption has a direct economic impact. Planning for maintenance can be complex, expensive and uncertain. Autonomous scheduling of maintenance jobs is essential. The design strategy of a novel integrated system for automatic job scheduling is presented; from concept formulation to the examination of the data to information transitional level interface, and at the decision making level. The underlying architecture configures high-level fusion of technical and business drivers; scheduling optimized intervention plans that factor-in cost impact and added value. A proof of concept demonstrator was developed to validate the system principle and to test algorithm functionality. It employs a dashboard for visualization of the system response and to present key information. Real track incident and inspection datasets were analyzed to raise degradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum scheduling was realized through data analytics and job sequencing heuristic and genetic algorithms, taking into account specific cost & value inputs from comprehensive task cost modelling. Formal face validation was conducted with railway infrastructure specialists and stakeholders. The demonstrator structure was found fit for purpose with logical component relationships, offering further scope for research and commercial exploitation.

The Role of Leadership in Implementing Lean Manufacturing

Procedia CIRP, 2017

It is widely accepted that for the successful implementation of lean manufacturing, the senior ma... more It is widely accepted that for the successful implementation of lean manufacturing, the senior management commitment is of great importance. However, the lean journey is usually a long one, and eventually management commitment creeps. Furthermore, the involvement of employees in daily improvements is also critical for the success of implementation. Lean leadership can be considered as a way of sustaining and improving the employee performance in lean production systems. In the present study, a thorough literature review is presented focusing in reviewing the principles of lean leadership and the practices that can lead in improving the employee performance. Furthermore, the characteristics and qualities of lean leader are discussed.

Lean Implementation Frameworks: The Challenges for SMEs

Procedia CIRP, 2017

Implementation of lean manufacturing in any type of organizations can bring many benefits, such a... more Implementation of lean manufacturing in any type of organizations can bring many benefits, such as reducing waste and improving operating efficiency. However, lean implementation is not a straightforward process. Although a number of frameworks have been presented, still many companies find it difficult to implement lean. Furthermore, most of these roadmaps are for large manufacturing companies, and not for small and medium enterprises. Unfortunately, there is not a recipe that if used can guarantee a successful implementation. Furthermore, unsuccessful implementation can have a great impact on organization's resources, but even more importantly, affect employees and their confidence in lean philosophy. In the present paper, the most prominent lean implementation frameworks will be discussed, under the prism of the needs of SMEs. The challenges for the SMEs in their lean journey are discussed.