18. On the Usability of Open-Source Machine Tools

Open-source hardware is a section of open-source and follows the general principles of open production (Redlich & Wulfsberg, 2011). Open-source hardware is defined by the Open Source Hardware Association as follows: “Open-source hardware is hardware whose design is made publicly available so that anyone can study, modify, distribute, make, and sell the design or hardware based on that design” (OSHWA, 2022). Similar to open-source software, open-source hardware benefits from increasing online collaboration. Designs of open-source hardware are being developed all over the world, shared digitally and replicated locally (Boujut et al., 2019).

The concept of open-source machine tools (OSMTs) as such was first introduced by Omer et al. (2022). Omer categorizes OSMTs as machine tools that have been developed and made accessible in an open-source manner. OSMTs form an important part in the further development of open labs, for example, as foundations of the Open Lab Starter Kit (Open Lab Starter Kit GitLab, 2022). Since the concept of OSMTs as such is still rather new, no subsequent studies in this field have been published. Therefore, no studies have been conducted on the usability of OSMT.

The term usability is defined as the “extend, to which a system, product or service can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use” (Deutsches Institut für Normung, 2018). However, the DIN norm keeps the definitions and concepts rather general, with no specific focus on the usability of machine tools (Deutsches Institut für Normung, 2018).

In general, usability of machine tools outside the open-source context is also a field that has not gotten much research attention. Studies on usability of machine tools mainly focus on the improvement of technical functionality (Brecher et al., 2011), or on the improvement of effectiveness and efficiency of processes as stated in the DIN EN ISO 9241-11 by Deutsches Institut für Normung (2018) Recently, problems of usability of machine tools have arisen due to an increasing complexity caused by higher degrees of automatization and digitalization in industry described by Puschmann et al. (2019). The authors focus on occurring errors during the use of machine tools and recommend rule-based error prevention to deal with this issue (Puschmann et al., 2019).

One related aspect which is often considered when talking about human errors and usability is the cognition of users. Cognition is defined by Wogalter et al. (2012, p. 871) as a “core area of psychology that is concerned with mental processes such as attention, memory and decision making”. Usability assessment and testing often focus on this cognitive area of the users. Practices such as a cognitive task analysis (CTA) or a cognitive walkthrough are common methods to determine the usability related to human actions, for example, for websites or interface testing. Those practices focus on the way a user describes and interacts with different tasks (Sharit, 2012; Vu et al., 2012).

Another area of usability studies focuses on users and their emotions related to the use of a machine: affective engineering and design. The field, however, mainly covers consumer products (Helander & Khalid, 2012). One area of affective engineering is Kansei engineering, which uses semantic methods to analyze the user’s emotions towards a specific design or product (Helander & Khalid, 2012). Liu et al. (2013) describe a first approach studying the design of machine tools based on Kansei engineering.

Combining these areas, Camerer et al. (2005) introduced a two-dimensional characterization of neural functioning which divides the neural activities of a person into cognitive and affective processes which either happen in a controlled or an automatic way. Helander and Khalid (2012, p. 572) highlight the importance that “cognition must consider affect or emotion and vice versa”.

Previous work describes a field study in the industrial sector of machine tools, concluding with the concept that not only affective and cognitive systems must be considered together, but that also the technical system as such is an essential part of overall usability. During this study, several different partners from industry, including machine tool developers and machine tool educators have been interviewed with regards to their perspective on usability issues of digital machine tools. In addition to the interviews, user observations had been carried out. In this study, the interaction between the technical, the cognitive and the affective dimensionhave been explained and determined. For further details see Lange et al. (2023).

The technical dimension comprises all influences with regards to software and hardware functions of digital machine tools. Among others, it includes the influence on the factors of machine tool complexity, the number of parameters and their proper settings, interface design, frugality of the machine tool, and the level of automatization and digitalization. The cognitive dimension includes all processes that a user goes through whilst using a digital machine tool. This includes the factors of a general process understanding, pre-knowledge about the machine’s functionality, the learning and teaching process, as well as previous experiences whilst using digital machine tools. The affective dimension covers all aspects related to emotions. This includes negative emotions such as fear of operating the machine incorrectly, as well as positive emotions such as motivation, trust, pride or a feeling of safety, whilst using the machine tools. Furthermore, the importance of considering the interconnectivity between these dimensions is highlighted. Factors associated with machine tool usability are not only affected by one of the dimensions but are rather interconnected between the three dimensions and influenced by all of them (Lange et al., 2023).

It is important to note that these dimensions have been consolidated in an industrial context. The authors used this basis to create a connection to the open-source context. Therefore, the following research question arises: which socio-technical factors influence the usability of open-source machine tools, and how can they be categorized along the three dimensions to generate a holistic approach on OSMT usability?

The factor of process understanding is probably the most significant aspect in regard to usability. According to the interviews, the fact that users have the need to understand what is happening when using the machine remains undoubtedly one of the core influences on the later usability of a machine tool. Here, one aspect in the open-source context has a great impact on the process understanding: the ability of actual participating in the replication and building process of an OSMT. When users actively participated in the building of machine tools, different educators have noticed a deeper process understanding on their side:

Simply the understanding of the interconnection within the machine increases. Because they have now assembled it themselves. So, for example an end stop sensor was attached somewhere and this end stop sensor was connected via a cable and then connected to the 3D printer control board. (OSMT educator)

Even if users are not actively involved in a building process, the understanding of it can be increased by the openness of the documentation and, for example, an easier insight into maintenance and repair works.

Process understanding is primarily associated with the cognitive dimension of usability. However, it is also connected to the other two dimensions. The technical dimension influences the factor of process understanding. A simpler and less complex product design also facilitates the process understanding as such. The affective dimension, in return, is influenced by the factor of process understanding. A higher process understanding leads to the user’s ease within the affective context. An alteration in each of the dimensions directly influences the overall usability of the OSMT. This interconnection is visualized in Fig. 18.1.

Machine tool complexity is a factor that has come up in the industrial as well as the OSMT context. This factor is largely connected to software and hardware design of machine tools. However, the focus during the development process in the open-source environment is currently mainly set on a machine’s functionality. Also, developers stated that they have to use whichever software or hardware solution is available open source. This leads to an increasing complexity of the final OSMT. One developer describes the problem as follows:

We need three softwares. And it would be much better if it was just one. But what can we do? [...] If you don’t have someone to code and do something specifically for your needs, you have to deal with these Frankensteins. (OSMT developer)

However, some of the OSMT developers are already aware of this situation and try to come up with possible solutions to minimize the complexity for the final OSMT user:

Just minimize all of the possibilities of them doing the wrong things by minimizing the components they can interact with. Building things in the background, so the consumer doesn’t even know they are there and making them look nice and intuitive. (OSMT developer and usability expert)

The factor of machine complexity is mainly located in the technical dimension. However, it largely influences the cognitive and affective dimension. A higher complexity leads to a larger effort in process understanding and at the same time lowers the ease within the affective dimension. The interaction between the factor and the dimensions is also shown in Fig. 18.1.

Another aspect that was mentioned several times in the interviews was the focus on the community and the importance of the prevailing mood that an open lab environment creates for users. By creating an atmosphere where trial and error is part of the game, users are encouraged to perceive OSMTs differently. Many users and developers mention the fear of “breaking the machine” that often occurs during first interactions of users and machine tools. However, the open-source context focuses more on engaging users in the process of creating, maintaining, and optimizing the machine tools, helping the atmosphere of learning and curiosity.

With regards to the three dimensions, the prevailing mood falls within the affective dimension whilst also influencing the other two dimensions (technical and cognitive) as shown in Fig. 18.1. The open-source community has a strong impact on the development process of OSMTs. Developers, for example, try to consider the social backgrounds of users or the way users react to machine issues. This aspect indirectly influences the development process of OSMTs and therefore also the technical dimension. The learning environment which is created in open labs – highly connected to the cognitive dimension – is also influenced by the general atmosphere within an OSMT context.

The three identified main factors shown in this chapter have been described by way of examples. However, each of the other factors listed in Fig. 18.1 can and should also be considered in the context of OSMT usability. In general, this concept shows how the three dimensions (technical, cognitive and affective) can be considered when specific factors that influence the usability of OSMT are dealt with. Developers, educators and lab managers should keep this holistic view on the interconnection between the dimensions in mind when working with or on OSMTs.