Below you can find a list of all the publications available to download.

Articles and Whitepapers

Title: IIoT case study. Data transfer and collection

The recent increase of interest in IoT is seen as an opportunity as well as a risk. The domestic consumer market is more flexible to the introduction of IoT as demonstrated by the fleet of IoT devices available. Industrial environments are much less inviting due to their restrictive nature. There are few reasons which include security, robustness, and ease of integration of these systems.There is a difference between IoT and industrial IoT (or IIoT). While IIoT can be seen as a subset of IoT, it is different in terms of application requirements, objectives and complexity. While domestic IoT devices are mostly focused on making life easier, IIoT focuses on different areas such as operational equipment efficiency, preventative maintenance, traceability, etc. The potential is massive, but technology adoption is not as straightforward.IIoT is slowly being adopted into manufacturing facilities – especially amongst MNCs. Being so new, it poses different challenges to the pioneers in the field – be it integrators, factory owners or creators of IIoT solutions. This document outlines some of them using a real-life project as an example.

Title: Minimising Changeover Times in Manufacturing Processes

Every manufacturing process has periods of time where resources/machines are unavailable due to tooling changes, material changes, part changes, program changes. These events are referred to as “changeovers”, or alternately as “setup”, or “planned downtime”. Changeover times can last from a few minutes to as much as several weeks. Reducing the changeover times is a problem of interest as it will boost the plant capacity, and help increase overall output. There are many ways to reduce changeover times. Here in particular, we exploit the fact that the changeover matrix is asymmetrical (see fig 1). Changeover time between two products p1 and p2 is different from p2 and p1. For instance, if you are changing from dark chocolate ice cream to white milk ice cream, you must make sure the system is very carefully cleaned. Any smudge of dark chocolate remaining will stand out in the white milk ice cream. The other way around, however, will not be as much of a problem.

  Changing From
      Chocolate Raspberry        Milk
Changing To Chocolate   15 10
Raspberry 20   15
Milk 30 20  

Figure 1 (Changeover times in minutes)   A mathematical model based on the well-known traveling salesman problem is implemented in Python using Pyomo (open-source optimization modeling language). Optimal results are obtained by using open solvers such as CBC (Coin-or branch and cut) that exploit the mathematical model to find the best sequence of changeovers based on the constraints described by the model.

Title: Psychology in Manufacturing

Once a new software or machinery is developed and integrated in a manufacturing environment many issues arise around the interaction between the new technical system and its human users. The biggest concerns emerge around products’ usability and safety, and, even more important, user’s needs and motivations in adopting it. Only by investigating and addressing these concerns, a company can deliver not just an excellent product, but also an outstanding one. To be able to successfully face these issues it is essential to work alongside psychologist and user experience professional specialized in creating easy, comfortable and safe human-machine interactions while increasing user’s engagement. The IMR’s team includes psychologist and user experience experts, who are ready to support you in incrementing your company productivity and product’s quality, by improving your clients’ and operators’ overall experience.

Title: Cobotics

“Industrial automation and robotics are nothing new within manufacturing. However, a new paradigm is emerging which blends manual and robotic activities. Where traditional automation solutions have been isolated from the human workforce for safety reasons, new sensorised and aware robotic systems – or collaborative robotic systems (Cobotics) – are now becoming commonplace, allowing these systems to be integrated into the human workforce.   Now, for the first time, it is possible to combine the human and robot capabilities, expanding the reach of both. The flexibility offered by these Cobotics enables the robotic system to be repurposed quickly for various tasks according to the needs of the plant floor, changing the way we see automation. This, however, brings an additional complexity to automation design, requiring the consideration of the needs and behaviour of the operator, implying among other considerations a human-centric design aspect in automation.

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