Digital Toolkit for optimisation of operators and technology in manufacturing partnerships (DigiTOP)

Lead Research Organisation: University of Nottingham
Department Name: Faculty of Engineering

Abstract

The manufacturing industry, with the drive towards 'Industrie 4.0', is experiencing a significant shift towards Digital Manufacturing. This increased digitisation and interconnectivity of manufacturing processes is inevitably going to bring substantial change to worker roles and manual tasks by introducing new digital manufacturing technologies (DMT) to shop floor processes. At the same time, the manufacturing workforce is itself also changing - globally and nationally - comprising of an older, more mobile, more culturally diverse and less specialist / skilled labour pool.

It may not be enough to simply assume that workers will adopt new roles bestowed upon them; to ensure successful worker acceptance and operational performance of a new system it is important to incorporate user requirements into Digital Manufacturing Technologies design. In the past, Human Factors has shaped the tools used in manufacturing, to make people safe, to make work easy, and to make the workforce more efficient. New approaches to capture and predict the impact of the changes that these new types of technologies, such as robotics, rapidly evolvable workspaces, and data-driven systems are required. These approaches consist of embedded sensor technologies for capture of workplace performance, machine learning and data analytics to synthesise and analyse these data, and new methods of visualisation to support decisions made, potentially in real-time, as to how digital manufacturing workplaces should function.

The DigiTOP project will develop the new fundamental knowledge required to reliably and validly capture and predict the performance of a digital manufacturing workplace, integrating the actions and decision of people and technology. It will deliver this knowledge via a Digital Toolkit, which will have three elements:
i) Specification of sensor integration and data analytics for performance capture in Digital Manufacturing
ii) Quantitative analysis of the impact of four industrial Digital Manufacturing use cases
iii) Online interactive tool(s) to support manufacturing decision making for implementation of Digital Manufacturing Technologies

The DigiTOP project brings together a team with expertise in manufacturing, human factors, robotics and human computer interaction, to develop new methods to capture and predict the impact of Digital Manufacturing on future work. This project will work closely with a range of industry partners, including Jaguar Landrover, BAE Systems, Babcock International and the High Value Manufacturing Catapult to co-create industry-specified use cases to examine. The overall goal of DigiTOP is to produce a toolkit, derived from new fundamental engineering and science knowledge, that will enable industry to increase productivity, support Digital Manufacturing Technology adoption and de-risk the implementation of future Digital Manufacturing Technologies through the consideration of human requirements and capabilities.

Planned Impact

The key beneficiaries of this research will be a) the manufacturing industry, who will have deeper and more robust understanding of the potential benefits of implementation of Digital Manufacturing, and be able to anticipate the changes that this approach will bring to the workplaces and organisations that they deliver; b) companies developing technologies to support Digital Manufacturing, who will be able to tailor their products and guide their implementation in line with the empirically-derived guidance that DigiTOP will deliver; and c) the UK more widely, after the increase in productivity and ability to quantify the impact of digital manufacturing on the industrial workplace.

Our impact will be enabled through

1) creating a Digital Toolkit to catalyse the manufacturing industry as they move towards optimised and safe digital manufacturing technologies,
2) targeted and meaningful engagement with industry collaborators from across the product lifecycle, supply chain and sectors within manufacturing;
3) development of people and expertise, in industry and academia in a domain that is rapidly developing;
4) conducting quantitative analysis of economic and societal impact of our work; and
5) communicating our work to wide audiences, including government, policy makers and the public.

In addition to our project partners, we will utilise our extensive networks of industrial collaborators to ensure that the impact of DigiTOP is as wide-reaching as possible. In particular we will leverage the communities from within the EPSRC Funded Digital Manufacturing Network Plus 'Connected Everything' and the Robotics and Autonomous Systems network, to ensure that our work engages a range of academic and industrial colleagues. We will ensure that the activities from DigiTOP are communicated in an accessible manner and in particular will take advantage of expertise within the consortium of communicating work via the Computerphile YouTube channel.

Our project partners will become early adopters and advocates for our toolkit, the Digital Toolkit itself will be disseminated openly, and example datasets will be shared as open source.

Publications

10 25 50
 
Description The DigiTOP project demonstrated the potential for sensing technologies to be used to monitor and understand human-technology collaborative work in a manufacturing setting. The project delivered a toolkit to raise the profile of considerations of data integration, ethics and design for manufacturing systems.
Exploitation Route The tools are freely available for use by others to explain digital manufacturing and show how different sensing technologies can be used to design human-technology collaborative work.
Sectors Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Manufacturing, including Industrial Biotechology

URL http://digitop.ac.uk
 
Title A head mounted augmented reality design practise for maintenance assembly 
Description This is the experimental data used to examine the impact of different AR HMD modalities on task performance, system usability, and user safety 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/A_head_mounted_augmented_reality_design_practise_for_m...
 
Title A head mounted augmented reality design practise for maintenance assembly 
Description This is the experimental data used to examine the impact of different AR HMD modalities on task performance, system usability, and user safety 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/A_head_mounted_augmented_reality_design_practise_for_m...
 
Title Data supporting: 'The influence of augmented reality interaction design on Pilot's perceived workload and situation awareness' 
Description This work explored the potential for Augmented Reality (AR) rendering information superimposed over the flight deck to increase a pilot's situation awareness (SA). This emerging technology introduced novel human-computer interaction paradigms that would have impact on pilot's cognitive demands. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/The_Influence_of_Augmented_Reality_Interaction_Design_...
 
Title Human-Human co-manipulation data 
Description The shared data were filtered and manually cleaned. There are four co-manipulation trials, each one contains the following columns: 'rosbagTimestamp': Timestamp '# of samples'Force/torque signal: 'Fx', 'Fy', 'Fz', 'Tx', 'Ty', 'Tz' Object position: 'x.v', 'y.v', 'z.v', 'Rx.v', 'Ry.v', 'Rz.v', 'w.v' Follower right arm/forearm EMG: 'emg_RFsgl', 'emg_RAsgl', Object displacement (Cartisaian): 'disp_x', 'disp_y', 'disp_z'Time difference between two consequent timestamps 'step_size' The data was collected as follows: Two humans were asked to co-manipulate a load of 10 Kg (together). One human was acting like a leader, and the other one was asked to follow. The only allowed communication between the follower and the leader is through the haptic clues (measured using 6-axis force/torque signal). The follower had EMG muscle activity sensors on the right hand (arm/forearm). Finally, the object position was tracked using an eight-camera VICON system. All sensory data were synchronised using ApproximateTime synchroniser; hence, they have the same timestamp. These datasets were collected through a GitHub tool available at: https://github.com/Intelligent-Automation-Centre/bluebox. The tool is explained in more detail in Al-Yacoub et al. (2020).Reference:Al-Yacoub, A, Buerkle, A, Flanagan, M, Ferreira, P, Hubbard, E, Lohse, N (2020) (Accepted for presentation) Effective Human-Robot Collaboration Through Wearable Sensors. In the 25th IEEE Conference on Emerging Technologies and Factory Automation, Vienna, Austria, 8-11 September. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://repository.lboro.ac.uk/articles/dataset/Human-Human_co-manipulation_data/12942122/1
 
Title Human-Human co-manipulation data 
Description The shared data were filtered and manually cleaned. There are four co-manipulation trials, each one contains the following columns: 'rosbagTimestamp': Timestamp '# of samples'Force/torque signal: 'Fx', 'Fy', 'Fz', 'Tx', 'Ty', 'Tz' Object position: 'x.v', 'y.v', 'z.v', 'Rx.v', 'Ry.v', 'Rz.v', 'w.v' Follower right arm/forearm EMG: 'emg_RFsgl', 'emg_RAsgl', Object displacement (Cartisaian): 'disp_x', 'disp_y', 'disp_z'Time difference between two consequent timestamps 'step_size' The data was collected as follows: Two humans were asked to co-manipulate a load of 10 Kg (together). One human was acting like a leader, and the other one was asked to follow. The only allowed communication between the follower and the leader is through the haptic clues (measured using 6-axis force/torque signal). The follower had EMG muscle activity sensors on the right hand (arm/forearm). Finally, the object position was tracked using an eight-camera VICON system. All sensory data were synchronised using ApproximateTime synchroniser; hence, they have the same timestamp. These datasets were collected through a GitHub tool available at: https://github.com/Intelligent-Automation-Centre/bluebox. The tool is explained in more detail in Al-Yacoub et al. (2020).Reference:Al-Yacoub, A, Buerkle, A, Flanagan, M, Ferreira, P, Hubbard, E, Lohse, N (2020) (Accepted for presentation) Effective Human-Robot Collaboration Through Wearable Sensors. In the 25th IEEE Conference on Emerging Technologies and Factory Automation, Vienna, Austria, 8-11 September. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://repository.lboro.ac.uk/articles/dataset/Human-Human_co-manipulation_data/12942122
 
Title Hybrid recommendations and dynamic authoring for AR knowledge capture and re-use in diagnosis applications 
Description In Industry 4.0, integrated data management is an important challenge due to heterogeneity and the lack of structure of numerous existing data sources. A relevant research gap involves human knowledge integration, especially in maintenance operations. Augmented Reality (AR) can bridge this gap, but it requires improved augmented content to enable effective and efficient knowledge capture. This paper proposes dynamic authoring and hybrid recommender methods for accurate AR-based reporting. These methods aim to provide maintainers with augmented data input formats and recommended datasets for enhancing the efficiency and effectiveness of their reporting tasks. The proposed contributions have been validated through experiments and surveys in two failure diagnosis reporting scenarios. Experimental results indicated that the proposed reporting solution can reduce reporting errors by 50% and reporting time by 20% compared to alternative recommender and AR tools. Besides, survey results suggested that testers perceived the proposed reporting solution as more effective and satisfactory for reporting tasks than alternative tools. Thus, proving that the proposed methods can improve the effectiveness and efficiency of diagnosis reporting applications. Finally, this paper proposes future works towards a framework for automatic adaptive authoring in AR knowledge transfer and capture applications for human knowledge integration in the context of Industry 4.0. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Hybrid_recommendations_and_dynamic_authoring_for_AR_kn...
 
Title Hybrid recommendations and dynamic authoring for AR knowledge capture and re-use in diagnosis applications 
Description In Industry 4.0, integrated data management is an important challenge due to heterogeneity and the lack of structure of numerous existing data sources. A relevant research gap involves human knowledge integration, especially in maintenance operations. Augmented Reality (AR) can bridge this gap, but it requires improved augmented content to enable effective and efficient knowledge capture. This paper proposes dynamic authoring and hybrid recommender methods for accurate AR-based reporting. These methods aim to provide maintainers with augmented data input formats and recommended datasets for enhancing the efficiency and effectiveness of their reporting tasks. The proposed contributions have been validated through experiments and surveys in two failure diagnosis reporting scenarios. Experimental results indicated that the proposed reporting solution can reduce reporting errors by 50% and reporting time by 20% compared to alternative recommender and AR tools. Besides, survey results suggested that testers perceived the proposed reporting solution as more effective and satisfactory for reporting tasks than alternative tools. Thus, proving that the proposed methods can improve the effectiveness and efficiency of diagnosis reporting applications. Finally, this paper proposes future works towards a framework for automatic adaptive authoring in AR knowledge transfer and capture applications for human knowledge integration in the context of Industry 4.0. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/Hybrid_recommendations_and_dynamic_authoring_for_AR_kn...
 
Title The Influence of Augmented Reality Interaction Design on Pilot's Perceived Workload and Situation Awareness 
Description This work explored the potential for Augmented Reality (AR) rendering information superimposed over the flight deck to increase a pilot's situation awareness (SA). This emerging technology introduced novel human-computer interaction paradigms that would have impact on pilot's cognitive demands. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/The_Influence_of_Augmented_Reality_Interaction_Design_...
 
Title The Influence of Augmented Reality Interaction Design on Pilot's Perceived Workload and Situation Awareness 
Description This work explored the potential for Augmented Reality (AR) rendering information superimposed over the flight deck to increase a pilot's situation awareness (SA). This emerging technology introduced novel human-computer interaction paradigms that would have impact on pilot's cognitive demands. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
URL https://cord.cranfield.ac.uk/articles/dataset/The_Influence_of_Augmented_Reality_Interaction_Design_...
 
Description A Design Framework for Adaptive Digital Twins 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Online webinar, presented by an academic from one of the DigiTOP Partner Universities. 30 mins for a presentation and 15 minutes for Q&A to the presenter.
Year(s) Of Engagement Activity 2021
URL https://digitop.ac.uk/?page_id=4445
 
Description Connected Everything 2020 Summer School 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact We were delighted to partner with the Smart Products Beacon at University of Nottingham to deliver our 2020 Summer School. This 3 day event focused on how co-bots could support a post-Covid world. 25 postgraduates joined the online event with support from academics, researchers and industry. The final day saw the students present their co-bot solutions and a team was selected by a panel of judges as the most appropriate response to the brief.
Year(s) Of Engagement Activity 2020
URL https://connectedeverything.ac.uk/summer-schools-and-workshops/
 
Description Defence Sustainability Conference 2020 - 19th and 20th January 2021 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact In the first of its kind, the Defence Sustainability Conference will showcase the extensive work currently underway across the MOD, Industry and Academia to optimise operational advantage and support the target of Net Zero 50 (NZ50).

It will highlight the need for clear policy developments and provide a platform for innovative ideas and projects being delivered in support of a more sustainable future. This will include presentations from some of the key stakeholders both within the MOD itself, across the supply chain and outside of Defence. The event is designed to spark opportunities for developing best practice and collaboration, as well as creating a pan-sector network of stakeholders to help raise awareness of opportunities to challenge the current ways of working.

The keynote speeches for the day will be provided by Lieutenant General Richard Nugee CB CVO CBE Climate Change and Sustainability Strategy Lead and Lieutenant General Richard Wardlaw OBE, Chief Defence Logistics and Support, who will provide his vision on a Sustainable Defence operating model.
The conference is being run as a collaboration between Team Defence Information, UK Defence Solution Centre (UK DSC) and the Ministry of Defence, with support from ADS Group and techUK, and will feature a full day of live speakers, virtual trade stands and areas to network and share ideas.

John Erkoyuncu delivered the session - Design of digital twins in defence 3-4pm with Babcock
Year(s) Of Engagement Activity 2021
URL https://secure.teamdefence.info/community.php?community=1000135
 
Description Digitop seminar on Human Factors in Industry 4.0 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Public seminar on Human Factors in Industry 4.0. Raised awareness of the pros and cons of virtual reality in industrial applications.
Year(s) Of Engagement Activity 2020
 
Description EHF2020 'The digital footprint at work - human factors challenges and opportunities' by Prof. Sarah Sharples (keynote) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact The digital footprint at work - human factors challenges and opportunities
Professor Sarah Sharples, University of Nottingham, UK

As personal and workplace technologies develop, as HFE professionals we now have a vast range of tools available to aid our understanding and analysis of workplace experience and behaviour. However, this data presents challenges, in terms of how it is interpreted, how it is used to inform decisions, how we manage personal privacy and how we balance quantitative and qualitative data sources.

This short presentation will provide a short overview of the types of technologies currently being explored, and begin to consider two alternative futures - a utopian one, and a dystopian one. Participants will then be encouraged to raise and discuss questions about the future of 'technology-led' HFE and how we can use these technologies responsibly to influence safer and more effective workplaces, lives and societies.
Year(s) Of Engagement Activity 2020
URL https://conference.ergonomics.org.uk/cth_speaker/sarah-sharples/
 
Description Facial Thermography 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Online webinar, presented by an academic from one of the DigiTOP Partner Universities. 30 mins for a presentation and 15 minutes for Q&A to the presenter.
Year(s) Of Engagement Activity 2021
URL https://digitop.ac.uk/?page_id=4445
 
Description Lecture on Human Factors in Industry 4.0 on Digital Manufacturing 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Undergraduate students
Results and Impact Lecture to students on the Digital Manufacturing Level 4 module at the University of Nottingham, December 2022. Made specific reference to the Digitop toolkit, and to the Sensory Illusions research. Students demonstrated greater engagement with the subject area, as evidenced by their coursework submissions.
Year(s) Of Engagement Activity 2022
 
Description Lecture on Human Factors in Industry 4.0 on the Digital Manufacturing 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Undergraduate students
Results and Impact Introduced Human Factors challenges in Digital Manufacturing to students on a Manufacturing UG MEng course, and made specific reference to the Digitop Toolkit & the Sensory Illusions research. Students demonstrated an increased understanding of human factors challenges in digital manufacturing as evidenced by their coursework submissions.
Year(s) Of Engagement Activity 2020
 
Description Lecture on Human Factors in Industry 4.0 on the Digital Manufacturing 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Undergraduate students
Results and Impact Lecture to students on the Digital Manufacturing Level 4 module at the University of Nottingham, December 2021. Made specific reference to the Digitop toolkit, and to the Sensory Illusions research. Students demonstrated greater engagement with the subject area, as evidenced by their coursework submissions.
Year(s) Of Engagement Activity 2021
 
Description Manufacturing 2075 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact Keynote talk at Manufacturing 2075 event at Cranfield University
Year(s) Of Engagement Activity 2018
 
Description New technologies and measurement of biomechanical risk factors: Keeping employees' digital footprints under control 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presentation exploring potential for physiological and subjective measures for capturing real time industrial performance and experience
Year(s) Of Engagement Activity 2019
 
Description Structured authoring of AR based Communication 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Online webinar, presented by an academic from one of the DigiTOP Partner Universities. 30 mins for a presentation and 15 minutes for Q&A to the presenter.
Year(s) Of Engagement Activity 2020
URL https://digitop.ac.uk/?page_id=4445
 
Description Wearable Sensors in a Human-Robot Collaboration Context 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Online webinar, presented by an academic from one of the DigiTOP Partner Universities. 30 mins for a presentation and 15 minutes for Q&A to the presenter.
Year(s) Of Engagement Activity 2020
URL https://digitop.ac.uk/?page_id=4445
 
Description YouTube video "What is Digital Manufacturing?" 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact Members of the DigiTOP project team created an animated video aimed at school children which explains what is digital manufacturing. As of February 2023, the video is showing over 4,000 views.
Year(s) Of Engagement Activity 2021,2022,2023
URL https://www.youtube.com/watch?v=ptDJw98Ds9M&t=68s