Visualization and IT in product and production development

Project time: 2012 – 2015

Budget: 7 470 000 SEK

Funding: FFI – Strategic Vehicle Research and Innovation

The projects aim was to combine the technologies from virtualization to digitalize the methods from visualization in order to enable their usage in global teams as well as to create transparency between knowledge work and the management of the knowledge needed for the execution and improvement of that knowledge work

Project ”Visualization and IT in product and production development” (Vis-IT) was started to address the need to integrate two current trends in product and production development:
1. Increased virtualization and management of product and process data
2. Increased visualization of knowledge work concerning planning, deviation management, problem solving and knowledge management.
The project was set up in a cross-industrial and academic setting involving partners from automotive as well as medical technology industries supported with academic knowledge and a software supplier. The purpose of this set up was to apply and demonstrate the developed digital methods directly in industrial usage and through that generate feedback to enable quick learning and evolve both the methods and tools. This evolutionary approach was realized through a continuous development (or agile) approach called “vertical slicing” where each new addition to the digital methods and tools is first stated as a hypothesis, then developed with full functionality concerning both user interface, data processing logic and
FFI Fordonsstrategisk Forskning och Innovation | www.vinnova.se/ffi 4 data storage and employed to generate feedback in order to either prove or disprove the hypothesis based on actual usage. The following is a summary of the findings concerning the four different method categories that have been digitalized in the project:
 Visual planning
The conclusions are that the user acceptance for the digital tool is directly related to their ease of use (and not necessarily their ability to exactly replicate the wall-based analog method). There is a clear risk of introducing too much data management in the tool (for the sake of later capitalization of the data). Such an introduction leads to a loss of visibility and transparency as well as destroys the ease of use as the creation of plans becomes too administrative. There is however a risk of introducing too little data management allowing too much flexibility for the users to create their own planning standards. This too leads to a loss of visibility and transparency between different plans (e.g. project or line function plans). In addition too little or no data management also leads to a degradation of value of the digital tool as a certain level of data management is needed to allow added functionality (such as aggregation of an individuals commitments from different planning boards, filtering possibilities to improve visibility and possibility to do statistical follow-up of bottlenecks in the knowledge work based on plans and outcomes). The project has put much attention to the level of data management and automation to find the optimal spot in the method and tool that has resulted from the project.
 Visual deviation management (PULS)
Conclusions concerning the level of data management and automation are on par with the conclusions from visual planning also in deviation management. Additional knowledge was created concerning how to visually manage and represent the lifecycle of a deviation to make sure the deviation management meeting can fulfill its purposes of creating transparency and synchronization between the different organizational functions which typically participate in such PULS meetings. Also traceability to additional data concerning not only the status of the deviation but also concerning its resolution was needed to be integrated in the method and tool to fully benefit from the digitalization effort.
The main bottlenecks concerning the usage of this method (at least in the consortium) were found to be not in the method or its digitalization but in the training and policies concerning its usage (e.g. when and how to use, who to involve etc). For this reason no significant hypotheses and corresponding vertical slices could be extracted from the participating companies. It was found that the term checklists was quite wide spread in the participating companies but its usage was mainly of an administrative character e.g. checking in retrospect that simple administrative tasks mainly concerning documentation have been done for the sake of downstream processes. From a knowledge reuse point of view it was found that the checklist method as such is effective as it helps the user to focus on relevant decisions and tasks. It was however found that its simplicity is a limiting factor for a wider usage because of the inability to capture more complex engineering knowledge concerning interactions, correlations and dependencies between different components and/or physical phenomena. The hypothesis, which was successfully evaluated, concerned the idea to integrate the simplicity and visibility (mainly in terms of knowledge reuse) of checklists with the complexity of engineering guidelines and handbooks. The result was named engineering checksheets and both the method and the tool have been positively accepted by the users
Finally it is concluded that future research needs to focus on the integration of the four different methods to create a base of logically connected methods to achieve continuous improvement by connecting the planning and execution of knowledge work (through visual planning, deviation management and problem solving) with the management of the knowledge needed to execute and improve the knowledge work.

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