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The DigiTOP Toolkit is a collection of Good Practice, Data, and Resources

The Toolkit below is an example of current good practice in implementing digital manufacturing technology (DMT) and its implications for workers who interact with the technology.

You will find a repository for information, software, frameworks, datasets, and publications on the design of DMTs and their impact on individuals and joint-cognitive manufacturing systems.

Video: What are digital manufacturing technologies?

This is a short animated video that explains what digital manufacturing is. You will also see various digital technologies explained in a clear and concise way.

Transcript: What are digital manufacturing technologies?



Spoken text: In this video we're going to explain what digital manufacturing is. To start with, what is manufacturing? Manufacturing is making things on a large scale like in a factory. Factories started over a hundred years ago, before that things were made mainly by hand. A good example of this is building cars, when the car was invented it was built slowly part by part but then Henry Ford came along and worked out how to build cars more quickly and easily using a production line. Production lines and factories have changed to include digital technology things like robot arms which now help build cars. In the future manufacturing will use more and more of these digital technologies.

Spoken text: What is digital manufacturing then? Digital manufacturing is when computers are used to help with manufacturing, for instance humans and robots working closely together, computers testing things out before you have to try them, in the real world saving time and money. This is called the digital twin idea. Imagine your machine has a twin made from data that lives inside a computer. Whenever you're wondering what something might be like you could test it on the twin first. So you're wondering what would happen if you speed up a machine? You could try it on the digital twin, if things go wrong like a part of the machine gets too hot you know not to do that in real life. To take this a step further there's an idea called the digital brain.

Spoken text: In real life we learn from the things that happen to us, for instance playing with building blocks tells us that a tower needs a good base or it might fall over. We learn and hopefully remember so we won't make that mistake again. Digital brain tries to do this too. If it is part of a robot which is manufacturing an object and something goes wrong it learns what was happening at that time. What kind of material was it using? What else was happening? It takes this information and learns that there may be a problem if things are the same in the future, it remembers so it can try not to make that same mistake again. How do we communicate with the systems and robots in manufacturing? Should we press buttons? Can we tell them what to do? How quickly should the robots work? How will the robots know what we are doing? When humans work side by side with robots how they behave is important to us. If the robot moves too slowly the human could get frustrated waiting around for it, if it moves too quickly the human might get in the way. The robot may have extra strength to help the humans but this strength or force needs to be managed carefully to make sure the humans are safe.

Spoken text: But how do the robots know what the humans working next to them are doing? When humans and robots work next to each other they both need to know what the other is doing. Humans watch and listen to the robots to find out more, robots can use things like cameras to see and more advanced things like heart rate and breathing sensors. With this information the robot can make decisions. If the human seems to be relaxed based on their heart rate and other signs it might make different decisions than if it thinks the human is working too hard. An example might be the robot slowing down if it thinks the human is in trouble.

Spoken text: When things get really complicated it can be useful to use the internet to access what we call the "cloud". If there is a difficult manufacturing process it can speed things up to use a group of powerful computers with the internet. You don't always need to have your own powerful computers, you can borrow someone else's and use it through the cloud. Will robots take over manufacturing entirely? We think that robots and automated systems will be used to help humans manufacture things faster, greener and more cheaply than before. Digital manufacturing should be about people first and robots and automated systems should help them get their work done, however the more computers are used in manufacturing the more questions need answering. For instance, what happens to all the data that is produced, what could go wrong? How can we use digital manufacturing to make things better? What do you think about digital manufacturing?


DigiTOP Videos

Overview video of the DigiTOP project below presented by Advisory Board chair Ashutosh Tiwari

Transcript: DigiTOP Project - A viewpoint from Ashutosh Tiwari


Question, displayed as text on screen: What is your name, position/role and your institution?

Ash Tiwari: Hi my name is Ash Tiwari. I am Royal Academy of Engineering and airbus researcher in digital manufacturing at the University of Sheffield.

Question, displayed as text on screen: What is your understanding and experience with DigiTOP?

Ash Tiwari: I had the pleasure of chairing the advisory board of the EPSRC digital project. The program is really unique and exciting in many different ways, it's a multidisciplinary team to start with but what was really exciting about this project was that it had a focus on human factors in the implementation and development of digital technologies. A lot of current programs that we have in digital manufacturing have a very technological focus but DigiTOP project is unique because it starts with human factors and and the issues associated with human factors in the development and implementation of digital technologies. There will be huge impact of the outputs from the DigiTOP project and i think the main important impact would be that it would address the barriers to the adoption of digital technologies and industry. But it will go beyond it, it will actually optimize the outputs not just from the manufacturing system and technologies but also from the people and societies who work with it. So DigiTOP project is looking at the building of the whole system which is not only manufacturing system but also the people and the societies who contribute and run the manufacturing system.

Spoken question and displayed as text on screen also: What are some of the outputs from the DigiTOP project and how are they beneficial?

Ash Tiwari: DigiTOP project has come up with a number of toolkits and that's a real welcome development because that makes it easier for the outcomes of DigiTOP to be used by the manufacturing industry in the UK and beyond. I'll pick up one example of that. DigiTOP has come up with personas, personas are fictional characters that represent different types of users on the shop floor of digital technologies. Now what that allows industry to do is to look at the impact that digital technologies have on different types of users and how the interactions would work, and this type of analysis could help not only in designing of these digital technologies of the future but also in ensuring that they are implemented properly with maximum benefits both for the people and the manufacturing system. These outputs of DigiTOP are really exciting and would have an impact on the manufacturing industry and also on the economic system in general. I look forward to see how the results from DigiTOP are adopted by industry and look forward to collaborate with the DigiTOP team not only in industrial adoption but also in taking the research forward, thank you.

Below is a collection of short videos explaining the research and outcomes from the project, including the perspective and impact that the research has had within industry.

Video: Robotics and the Law: Towards responsible and sustainable adoption of industrial collaborative embodied autonomous systems in the case of digital manufacturing

Natalie Leesakul - Horizon CDT PhD

Video: The use of Personal Data in Automated Digital Manufacturing Environments

Joshua Duvnjak - Horizon CDT PhD

Video: Using Collaborative Robots and the effect on Operators in Digital Manufacturing

Subham Agrawal - UWE Bristol University

Video: The acceptance and adoption of digital manufacturing technologies and human factors

Anne-Marie Oostveen- Crafield University

Video: Understanding Human Performance and Cognition in Manufacturing with Physiological Sensing

Elizabeth Argyle - University of Nottingham

Video: Digital Readiness - Digital manufacturing technologies and industry

Brian Waterfield - Industry (Falmouth University)

Video: Digital Readiness - Digital manufacturing technologies and industry

Philip Jackson - Manufacturing Technology Centre

Video: Digital Readiness - Digital manufacturing technologies and industry

Steve Wilding - Industry (Babcock International)

DigiTOP Webinar Videos

Video Webinar: Wearable Sensors in a Human-Robot Collaboration Context.

Dr Ali Al-Yacoub (Loughborough University)

Video Webinar: Structured Authoring for AR based communication.

Dr Dedy Ariansyiah (Cranfield University)

Video Webinar: A Design Framework for Adaptive Digital Twins.

Dr John Erkoyuncu (Cranfield University)

Below are the different areas of the toolkit