This paper aims at conceptualising a digitised Shop Floor Management (SFM) visualisation board. The logic of inquiry throughout the study is an iterative back and-forth approach between our theoretical conceptualisation of the digitised visualisation board and empirical data collected in three industrial companies. The paper shows that digitised visualisation boards should have malleable representation capacities to transfer, translate and transform knowledge within and across SFM teams. A digitised visualisation board is suggested, which consists of; translating practices within SFM teams, translating practices across SFM teams, transforming practices across SFM teams and translating practices within SFM teams.

No abstract

No abstract

Smart manufacturing, an offspring from Industry 4.0 (I4.0), defines the future for the manufacturing industry. Smart manufacturing leads to digitalization of the shop floor, which is automated, computerized and complex. To stay competitive, digitalization of the shop floor management (SFM) boards will be instrumental in improving performance management and continuous improvement. The purpose of this paper is to improve the understanding of SFM board meetings in the era of I4.0. The paper explores the current adaptation level of digital SFM boards, and identifies influencing forces for and forces against a further transition from analogue to digital SFM boards. Based on a survey and a subsequent workshop with practitioners, this paper reveals that digital SFM boards have not yet been adapted at shop floor level, and currently, practitioners are stuck to the standardized procedures and manual processes. The forces against a further adaptation are a managerial mindset stuck in an Industry 2.0 era and immature technologies to digitize the visualization of real-time data. The forces for are the need of enhancing data transparency within and across teams, which means elimination of information silos and timeconsuming manual updates of SFM boards.

No abstract

This paper aims at emphasize the importance of digital decision support systems (DSS) to enhance the human based decision making at the shop floor management (SFM) level. This paper suggest that there is an increased focus on implementing digital technologies for developing DSSs that are adapted to the current threshold of the Industry 4.0 (I4.0) era. It is believed that there is a call for appliance of digital technologies for decision support, as the complexity of infrastructures at manufacturing facilities increases and the environments are becoming more uncertain. Those companies who not move rapidly and focus on being responsive will fall behind and lose market share, due to the large competition seen today. This paper suggest that the adaptation of digital DSSs at the SFM level will support the practitioners in their decision-making processes, wherefrom the performance level will increase.

The future of manufacturing is happening. Today’s cyber technologies allow real-time visual control of various production processes in manufacturing through the intelligent utilisation of data. Having access to knowledge is power. Providing shop floor practitioners with the opportunity to gain and share knowledge across boundaries in manufacturing in the right way at the right time is a prerequisite to doing a proper job controlling a production line. Carrying out shop floor operations without visual control leads to actions performed in blindness based on gut-feeling decision-making and is often prone to errors. This paper investigates a practical problem of securing knowledge integration across production units on the shop floor and managerial stakeholders via a digital visualisation tool (a visualisation board (VB)). The study constitutes an instrumental case study and follows a transdisciplinary engineering process, outlining a collaborative approach with practitioners across various disciplines in a large manufacturing company in the Renewable Energy sector. The findings illustrate an unsuccessful approach to designing and deploying a digital VB. The paper’s contribution is a set of lessons learned from an unsuccessful attempt that highlights the importance of socio-technical solutions to digital transformations as opposed to purely technical solutions.

Transdisciplinary research commences with exploratory research to understand and solve complex real-world problems followed by explanatory research to generate academic knowledge. This paper conceptualises transdisciplinary engineering through the lens of intervention-based research, which seems useful to solve societal problems when practical knowledge to handle the problematic situation contradicts solution proposals emerging from prevalent theories. The proposed model combines academic knowledge, practical knowledge, and artefact portraying the problematic situation into means to achieve the end, which when implemented transforms the problematic situation into the desired situation. To explicate the proposed model, the study draws on a longitudinal research conducted by the two authors of this paper. In this study, which focuses on designing digitalised solutions for data-driven decision-making at shop floor level, we faced serve research-related challenges. The academic knowledge revealed a clear picture of how to design the solution, but the practical knowledge exposed that the digital solution was merely an illusion; i.e. a gap between theories and practical understanding. The proposed model to handle this gap forwards the role of artefacts and suggests that artefacts, academic knowledge and practical knowledge rank alongside.