ASSET MANAGEMENT Display only what the user needs The “SEED - Solid value from digitalization in forest industry” (www.seedecosystem.fi) project was launched in the autumn of 2019, and forest companies opened their doors to application developers and research. The SEED ecosystem develops methods and tools for business-driven asset management and productivity improvement. The SEED ecosystem aims to demonstrate, through rapid experimentations (POC), solutions to the challenges described by industry, which can be further developed through user feedback through the collaboration of ecosystem actors, possibly even towards commercial implementation. The interviews conducted in the SEED project highlighted challenges in the availability and use of asset and maintenance information, as well as in the utilization of tacit information. As part of the project, role-based views were developed for field maintenance technicians and maintenance managers to support evidence-based fault diagnoses and equipment replacement decisions (Tervo, J. <strong>2021</strong>. Evidence-based decision making for maintenance and asset management. Master’s Thesis. LUT University). The user interface was designed based on the wishes and needs gathered from users, and its development continues in the SEED project. The POC application combines information from different information systems so that the user needs to spend as little time as possible searching for information (Figure 2). It is built around a universal and versatile search function that helps the users find just the information they need. Item-specific documentation and visualized system entries are readily available, and information can be searched by item name, location code, or keyword in description texts. The problem of data quality It is obvious that evidence-based decisionmaking requires high-quality data sources. However, event logs and descriptions are short at best, and too often information may not be passed on at all to maintenance technicians and subsequent shifts. There may be several reasons for this, such as rush, lack of expertise, technical difficulties with the systems, or insufficient incentives to make high-quality entries. Proper forms, data validation and user motivation are all key to ensuring complete and efficient information transfer (IEC 60300-3-2:2004). Users of the systems don’t like writing long description texts if they don’t see them bringing tangible benefits in their work. This problem should be solved with the use of an information system that incorporates the system entries and descriptions into decisions and rewards for quality entries later as problem-solving speeds up. On the other hand, the pursuit of higher quality records may also require a greater change in the workplace culture and incentives. Mobile interfaces, on-the-spot dictation, “speech-to-text”-technology, and other new technologies may also contribute to the quality and comprehensiveness of human recordings in the future. Future of evidence-based decision-making Businesses are becoming increasingly datadriven, and many kinds of dashboard and reporting solutions are emerging. Instead of static dashboards and standard reports, evidence-based asset management calls for specialized reports that can be produced ondemand, according to the information needs of the time. The data sources behind the reports need to be reliable, transparent, and accessible for rapid processing. Numerical data can be processed to KPIs and visualizations, and written text can be analysed with text mining and language technology tools. This approach already forms a strong basis to utilizing evidence in maintenance and asset management, but there is still lots of work to be done in finding the best possible ways to store and display different forms of knowledge. Linguistic analysis Figure 2. With the help of language technology, the search function works regardless of non-standard words, typing errors or abbreviations. 50 maintworld 4/<strong>2021</strong>
VIBRATION ANALYSIS THERMAL IMAGING ULTRASOUND MEASUREMENT EYESIGHT – HEARING – SENSITIVITY WE HAVE IN COMMON MASTER THE LANGUAGE OF YOUR MACHINERY WWW.ADASH.COM
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