Kunskapsförmedlingen Magnus Löfstrand
Professor of Mechanical Engineering, PhD
Project time: 2017 – 2018
Budget: 889 900 kr
Funding: SIP Produktion2030
The project focuses on economic and environmental sustainability and increased industrial competitiveness.
The project aims firstly to investigate the prerequisites for service business models and modelling to be adopted in real business situations. Secondly it aims to identify adaption needs an adapt aspects of a Örebro University predictive maintenance and availability modelling system, as well as systems by LKAB, Atlas Copco, Alkit & Mobilaris, to support the use of the service business models, substantially decreasing the business risk for the supplier.
In the first part of the project, the most important conditions for implementing service-based business models will be identified (exemplified between LKAB and Atlas Copco) and supported by other project partners.
In the second part, through further development of previous research, literature studies, and interviews with industry representatives, the project will investigate how to make partner’s various existing technologies function together, to support the development of service-based business offers and reduce risk.The technologies will also be further developed.
The project will identify main requirements for adoption of service business models and the demands on maintenance systems to ensure high availability and resource efficient production.
The project will also identify requirements for the combination of technologies for system availability modelling, updated using data analytics, applied on Atlas Copco drill rigs, and real-time tracking of assets within the LKAB mining production process, to support service business models.
The results will support future continued research, additional applicable results and publications.
2016 – 2016
The SAPPA project is about innovative cloud-based predictive and preventive maintenance systems, improving availability of products and production systems.
2014 – 2016
2017 – 2018
2013 – 2017
2015 – 2016
2015 – 2016
2017 – 2018
2014 – 2017
2015 – 2015
2017 – 2018
2014 – 2016
Every manufacturing company measure and control production performance with a system of KPIs. The aim of the SMART-PM project is to investigate and demonstrate new ways of collecting data, transforming data to information and introducing new decision tools based on valid information and economic models of the production systems.
2018 – 2020
2013 – 2016
RemProLife aims at improving the use of life-cycle information to achieve more efficient remanufacturing from economic and ecological perpectives.
2013 – 2016
2015 – 2015
2014 – 2017
2015 – 2016
Increased sustainability and cost effectiveness through improved strategic decision-making in production issues based on new metrics system for production and development.
2015 – 2017
2016 – 2019
2014 – 2014
2016 – 2016
2014 – 2017
2017 – 2018
2014 – 2017
2014 – 2018
2014 – 2017
2016 – 2018
2017 – 2021
With globalization and other megatrends as demographic changes and climate change, more knowledge is needed regarding production in an international perspective. PADOK Study Visit in India 2016 have given an increased knowledge regarding how production is conducted in India, some of the challenges producing companies in that region is facing and how Swedish companies interested in investing in production in India could act to establish themselves in the region.
2016 – 2016
2017 – 2018
2017 – 2018
2015 – 2016
2016 – 2016
2015 – 2016
2013 – 2016
2015 – 2018
2016 – 2017
2017 – 2019
2013 – 2017
SeeCut focuses on cost-efficient production systems for secure collection, analysis, visualization, storage and sharing of production data. The project addresses the integration of new signals and sensors. For advanced products, like jet engine components, collecting data during manufacturing and usage is essential for quality assurance and remanufacturing. The project goals are to identify key technical requirements related to production data for use in digitalized value chains, define means to ease the run-time integration of new signals and data streams from manufacturing machinery and sensors, and define how to securely and cost-efficiently share data through the value chains in circular production.
2019 – 2019
2015 – 2016
Reduced lead times and improved performance for tooling through innovative manufacturing and assembly strategies as well as optimised design enabled by use of additive manufacturing (AM).
2016 – 2018
2016 – 2016
2017 – 2018
2015 – 2016
2015 – 2016
2014 – 2017
2017 – 2018
2015 – 2016
2017 – 2020
2017 – 2018
2015 – 2016
2016 – 2018
Tooling constitutes a significant part in the economical investment of the hot stamping process. Significant benefits in production economy and environmental benefits can be attained by improving the tribological performance in hot forming operations of automotive components. The main idea of this project is to create tailored tool surfaces on dies made from cheaper and easier to manufacture tool steel for the hot stamping of ultra-high strength steels.
2015 – 2018
2015 – 2017
2015 – 2016
2016 – 2017
2017 – 2020