H2020Индивидуална стипендия2017–2019

LeaD4Value · Lean data management for maintenance value

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2017-09-01 → 2019-08-31
Финансиране от ЕС: 195 455 €
Участници: 1
Схема: MSCA-IF-EF-ST

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Накратко на български

Управлението на данни при поддръжката на инфраструктура, като например пътища и мостове, се анализира за избягване на излишна информация. Това помага за вземане на по-добри решения и по-ефективно използване на ресурсите при ремонт на остарели съоръжения.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Lean data management for maintenance value

We live in a world being transformed by data and digitalization. Modern, advanced technologies are producing more and more data. This creates vast opportunities for data-based decision making and innovations, however it also causes new kind of challenges. Decision makers are often drowning in the data overload, and are not able to convert the data into valuable knowledge and finally into better decisions. The “Lean Data management for maintenance Value” project (LeaD4Value) addresses the problem from the perspective of maintenance and asset management. Maintenance is often seen as “necessary evil”, but its importance in keeping engineering and infrastructure assets safe and productive is crucial. Europe is suffering from a significant maintenance backlog because most new manufacturing investments are directed to other continents. This has resulted in not only relatively old equipment and facilities in the private sector, but also in deteriorating public assets, for instance unsafe roads and bridges, as well as schools or hospitals damaged by mould. It is important to find new, smarter ways to produce maintenance services. Data-based maintenance decision making can contribute to this issue, and that is why it is important to develop new managerial tools and methods to support the valuable and resource efficient use of data in maintenance. The main objective of LeaD4Value was to show how the business value of industrial maintenance can be maximized through adopting data-based decision making. This included studying the existing and potential data exploitation paths and their business value in maintenance organizations, and developing lean maintenance data management processes to prevent data overload. The big data hype has led many organizations into gathering a lot of data without proper plans for using it. The research conducted in this project showed that the value of data should be assessed to ensure that the additional benefits exceed the costs caused by collecting, storing, and analyzing the data.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

The possibilities of data-based maintenance management as well as interconnected, smart, and autonomous assets have been discussed lately but in practice there are still a number of major problems regarding e.g. the amount, quality, integration, and exploitation of maintenance data. In LeaD4Value these problems are addressed through lean maintenance data management to realise increased business value. Contrary to the Big Data hype, the idea here is to focus on the data decision support tools to be constructed based on analytical modelling and statistical analyses. Data will be collected from computerized maintenance management systems and enterprise resource planning systems of the two seconded companies, as well as from some of their employees via surveys and interviews. The results include e.g. a map of data exploitation paths, a process model, and a performance measurement system for lean maintenance data management. These tools can be used to reveal unnecessary maintenance tasks and data collection, missing data collection, or potential to increase the business value of maintenance. The role of world-class maintenance is highlighted in European manufacturing, because a majority of new production-related investments are directed to other continents. The proposed work is multidisciplinary by nature, combining aspects of business value management, reliability and maintenance engineering, and data sciences. The multidisciplinary view is needed, for asset management is challenged by maintenance engineers and managers understanding the technical aspects of maintenance but being unable to communicate these to the company decision makers in terms of business value. Too often this leads to short-sighted decisions. The project will expand the competences of the fellow in multiple disciplines, and provides international experience in science and business.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITY OF SUNDERLAND · SunderlandКоординаторОбединеното кралство