Data-rich environments and danger of information overload

In order to achieve new levels of efficiency and productivity, a lot more data will be collected and analysed as a part of the digital transformation in the industry. In the new intelligent factories multiple systems and devices will be interconnected and able to generate more data than ever before, therefore they are referred to as ‘big data’ (figure 1). Moreover, the generation of this big data expands much further than just the manufacturing process itself, but is also created during marketing, sales, maintenance and service processes [1]. And although it promises an opportunity for quick defect detection and better quality products, this is also one of the biggest challenges that Industry 4.0 will bring. From a human factors perspective, such as an increase in data, that needs to be understood and analysed before decisions can be made, could easily lead to information overload, which counteracts its benefits. To make sure that we make the most of the ‘big data’ in Industry 4.0, we must consider a question: How can we assist people working in new data-rich environments and help them solve problems and make decisions?

Figure 1. Big data creation through interconnected things of Industry 4.0

Photo credit: Salesforce.com, https://www.salesforce.com/uk/blog/2016/09/what-is-industry-4-0.html

According to Mengis and Eppler [2] information visualisation could hold a key to minimising cognitive load by delivering and arranging information in an alternative way – through the use of two or three dimensions and elements such as shape, colour, and texture. According to the authors, visually presented information can ease information retrieval and allow even novice users to process data to the same capability as experts would. It is not hard to imagine how this scenario could extend to the manufacturing floor – there is potential to have Ipads, smart watches and computer screens displayed all over the manufacturing plant and requiring attention from managerial and shop floor workers, as discussed and illustrated by Posada et al. [3] (figure 2), some of which might be new or in training. All these devices will be used to project the necessary information in real-time to be analyses and actioned upon.

Figure 2.Graphic representing operators exposure to various challenging technology (Posada et al., 2018)

It is evident that more research should look at decision making, problem solving and information visualisation for manufacturing context.

As part of my PhD and collaboration on Digitop’s WP5, I plan to further investigate information visualisation for Industry 4.0 technologies. It is important to find out what guidelines or tools could help envision and aid the design of future technology that is considerate of data overload and complexity of information that is being provided to human workers, as well as to understand the process of decision making and situation awarness in a shop-floor context. Only by gaining better understanding of these topics can we help design visualisations for these tools that fully support human operators, provding the needed information that is used effectively, and is an aid rather than a burden.

Laura Bajorunaite
PhD Student
University of Nottingham

References:

[1] Zhou, J., Yao, X. and Zhang, J. (2017). Big Data in Wisdom Manufacturing for Industry 4.0. 2017 5th International Conference on Enterprise Systems (ES).

[2] Mengis, J. and Eppler, M.J. (2012). ‘Visualizing Instead of Overloading: Exploring the Promise and Problems of Visual Communication to Reduce Information Overload’, in Strother, J.B., Ulijn J., Fazal, Z. (ed.) Information overload: an international challenge to professional engineers and technical communicators. John Wiley & Sons, Inc., pp.-203-225. [3] Posada, J., Zorrilla, M., Dominguez, A., Simoes, B., Eisert, P., Stricker, D., Rambach, J., Dollner, J., Guevara, M. (2018), Graphics and Media Technologies for Operators in

Main Image by Tumisu from Pixabay

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