Ramentor is one of the educators in World Class Maintenance training program


With the acquisition of Ramentor, AFRY further strengthens its digitalization capabilities and advances RAMS offering for clients. By using RAMS, AFRY can help clients make more informed decisions, optimize their risk level and overall life-cycle costs and support them in their digital transformation to more sustainable and cost-efficient solutions.

- RAMS engineering and consulting services are foreseen to be increasing in the coming years and are a key part of our energy and industry markets transition strategy. By integrating RAMS to current industry technical design practices we will create a unique differentiator for our services, says Richard Pinnock, Head of Division Energy, AFRY.

- We are excited to be part of AFRY. We have two decades of solid R&D and pragmatic industry project history on dependability management, and the market is clearly maturing now along with digitalization. Together with AFRY we can take our services to the next level by adding a significant global client base and support in future engineering and digitalization, says Timo Lehtinen, Managing Director of Ramentor.

Get to know Ramentor's products, trainings, application services and customer cases.

Afry Newsroom: https://afry.com/en/newsroom/press-releases/afry-acquires-software-and-expertise-company-ramentor-in-finland

Ramentor Oy is one of the company partners in the SMARAGDI consortium, which aim is to develop intelligent solutions for future high-temperature superconducting (HTS) magnets. The public-private consortium advances magnet technology and updates an experimental facility for testing HTS magnets in Tampere, Finland.

Ramentor's research focuses on reliability modelling of magnet manufacturing process and design of condition monitoring. The aim is to develop powerful analysis approaches that are applicable also to various other industry sectors. For complex systems, the combination of advanced modelling solutions and automatized data collection is required to enable calculation of useful analysis results without excessive workload.

"At Ramentor, we are developing modeling tools to analyze the condition monitoring needs in challenging systems. Fast data analysis can improve the machine reliability and increase its efficiency. Ramentor will support the TAU research in condition monitoring,” explains managing director Timo Lehtinen.

Business Finland has granted 1.2 M€ to the SMARAGDI consortium. The total value for the 2-year joint effort of Tampere University (TAU), 3DStep, Teraloop, Ramentor, Meluta, and Luvata is 2 M€. The long-term goal is to put Finland at the forefront of HTS magnet development when the technology fully breaks through to commercial applications.

More information can be found from the project website: https://projects.tuni.fi/smaragdi/

Jussi-Pekka Penttinen's (second from the right) doctoral thesis was publicly examined on 4 September 2020. The opponents were professor Jørn Vatn (on the left) from Norwegian University of Science and Technology, and professor Jaan Raik from Tallin University of Technology. The custos was professor Kari Koskinen (on the right) from Tampere University.

The Large Hadron Collider (LHC) in European Organization for Nuclear Research (CERN) is one of the most challenging targets in the world for reliability analysis. Only by using an efficient and flexible modelling technique it is possible to understand all the details affecting the operation. The same powerful approach can be used for increasing the production and energy efficiency of industrial processes.

As a part of the Future Circular Collider (FCC) study, CERN, Tampere University and Ramentor Oy developed a novel reliability modelling approach that is suitable especially for vast and complex analysis targets. The research focused on enabling automatized model creation and on ensuring diverse applicability and sufficient calculation speed. The result of the research was an OpenMARS approach, which was published in a peer-reviewed article.

In his doctoral dissertation M.Sc. (Tech.) Jussi-Pekka Penttinen has developed the OpenMARS approach further to act as a framework for customized reliability, availability and risk analysis tools. The framework supports fast and efficient development of a tool that adapts to the domain-specific needs of the analysis target, automatizes the model creation, and optimizes the calculation speed of analysis results. When compared to traditional tools, the use of a customized tool is significantly more user-friendly and the workload of the analyses can be managed better.

The dissertation is available online at:
http://urn.fi/URN:ISBN:978-952-03-1635-8

Väitöstiedote suomeksi:
https://www.tuni.fi/fi/ajankohtaista/uusi-kayttovarmuuden-mallinnustapa-mukautuu-analysointikohteiden-erityistarpeisiin

Arto Niemi's (on the right) doctoral thesis was publicly examined on 17 April 2019

In 2014 Ramentor started a co-operation with Tampere University and CERN to research methods and tools for reliability and risk assessment of particle colliders. The research is a part of Future Circular Collider (FCC) study, which develops scenarios for post-Large Hadron Collider (LHC) era. ELMAS was selected as a tool for model the collider systems and to simulate the particle acceleration process. The model enables assessing availability and collision production, which are essential quality attributes of a particle collider.

An ELMAS model of CERN's particle collider was created by M.Sc. (Tech.) Arto Niemi. In his doctoral dissertation “Modeling Future Hadron Colliders’ Availability for Physics” he validates the model against LHC operations and shows preliminary results on the FCC availability and collision production.

Mr Niemi's work for creating the particle accelerator's ELMAS model formed a foundation for a R&D agreement between CERN and Ramentor. The target was to develop an approach that allows combining the most common risk assessment and operation modeling techniques for efficient analysis of complex system with dynamic operation changes. In 2017 the FCC Innovation Award was given to the research. In 2019 Ramentor, Tampere University and CERN published the developed OpenMARS approach in a peer-reviewed article.

The dissertation is available online at http://urn.fi/URN:ISBN:978-952-03-1057-8

ELMAS version 4.9 has been released. Since the previous version ELMAS 4.8, following new features have been included in the software:

The full list of all changes can be found from below (unfortunately only in Finnish).

Click here to read Maintworld 4/2018

FCC Innovation Award Trophy FCC Innovation Award Poster

CERN Future Circular Collider Study (FCC) had 3rd annual meeting between May 29 and June 2 in Berlin. During the FCC Week 2017 the FCC Study Innovation Awards were given to celebrate and honor the most exciting tech and scientific developments in the FCC collaboration. The year 2017 award was given to Jussi-Pekka Penttinen, who is a doctoral student in Tampere University of Technology and works also as a chief architect of the ELMAS software in Ramentor. The award goes for the design work on an open and scalable modelling and simulation platform to understand and optimize the reliability, availability and energy efficiency properties of the particle accelerator complex.

The work is not only essential for the design of a future collider, but it efficiently leverages the existing infrastructure at CERN and can also find many applications in the industry. A large internationally active energy supply company got interested in the work on FCC to apply the method and tool for design work of a new type of liquefied natural gas (LNG) terminal. Also, for example, reliability of paper machine components, availability of data center infrastructure, and failure tolerance of final disposal facility for spent nuclear fuel have already been analyzed with the approach.

IoT

The upcoming digitalization puts more and more emphasis to Industrial Internet of Things (IIoT), which brings both opportunities and challenges for the management of business services and maintenance functions. These opportunities and challenges are discussed by experts from different Finnish industrial companies in a new book published by Finnish Maintenance Society, Promaint.

The upcoming digitalization puts more and more emphasis to Industrial Internet of Things (IIoT), which brings both opportunities and challenges for the management of business services and maintenance functions. These opportunities and challenges are discussed by experts from different Finnish industrial companies in a new book published by Finnish Maintenance Society, Promaint.

Ramentor acts as one of the expert groups representing various technical solutions for IoT management. A book chapter that is provided by Ramentor explains through practical examples how IoT deployment can be executed as effectively as possible in cases where the previously collected data in the organization has inadequate quality.

The book is available unfortunately only in Finnish. It can be bought from: http://promaint.mycashflow.fi/product/10/teollinen-internet-uudistaa-palveluliiketoimintaa-ja-kunnossapitoa

Training

World Class Maintenance training program, organized by AEL, is an advanced three-month education for supervisors, designers and managers working in the Finnish maintenance sector. The purpose of the training program is to coach Finnish maintenance experts to use certified and the most efficient maintenance management techniques in their work.

Ramentor's role in the training program is to provide material for the education and to act as one of the training program educators. The program includes many Ramentor's expertise-specific topics like different risk management methods and analysis tools used for RAMS management and development.

Ramentor offers also customer-specific RAMS trainings for everyone looking to increase their knowledge on RAM and its management. These customized trainings can include e.g. basics of RAMS or more advanced know-how on RAMS development and different analysis tools (e.g. FMEA, RCM, FTA and RBD) used for it.

One great example of a customized RAMS training is the package created for CERN.