The benchmarking tool Smart Maintenance Assessment (SMASh)

​50 percent of the capacity in the Swedish manufacturing industry is unused, which is largely due to disruptions in production. Here, smart maintenance plays an important role in increasing the efficiency of the machines and meeting the sustainability challenges of the future. Smart maintenance means working with data-driven decision-making, elevating human capital resources, and integrating the maintenance organization both within the company and with external actors.

Smart Maintenance Assessment (SMASh)

The benchmarking tool Smart Maintenance Assessment (SMASh) has been developed by researchers at Chalmers together with Swedish industry. SMASh consists of a web-based questionnaire that is answered by maintenance managers and employees. The questions take approximately 30 minutes to answer. Access to the questionnaire is provided through the website: http://digitalsmash.se

In the end of this article you can also find generic tips on how to be successful at Smart Maintenance

Interview with the researchers Anders Skoogh and Jon Bokrantz

“Of course, you need a technical digital capacity to enable data-driven decision-maing. But what we find in our research is that if a factory isn’t simultaneously investing in the development of the whole organization, the data will not be of much use and a lot of value creation will be lost”, says Anders Skoogh researcher at the Division of Production Systems.

Smart maintenance means that the maintenance decisions are based on analyzes of operational data. The decisions can be both automated and function as a complement to human decision-making. The level of data-driven decision-making today is generally low in Swedish industry which means that there is a great potential for development regardless of industry and size. An increase in a factory's levels of data-driven decision-making contributes to a better maintenance performance regardless of the current level, so it is always beneficial to start. The effectiveness of data-driven decision-making is related to the quality of the collected data, and how well it can be analyzed and integrated within the company and external partners.

“The competence of the maintenance staff is crucial when working with data-driven decision-making. It’s both about collecting good quality data, and that it can be analyzed in a competent way. IT tools must be part of the daily operations and the maintenance staff will also have to work in larger networks both inside and outside the company. There are no easy shortcuts, you must work systematically and gradually to build a functioning structure”, says Jon Bokrantz, researcher at the Division of Production Systems.

Another effect of industrial digitalization is that boundaries, both within and between organizations, becomes increasingly vague. This can be used to strengthen the effects of data-driven decision-making by making the maintenance organization an integral part both in the company and with external partners.

“When factories start working with smart maintenance it’s natural to start with competence development and a gradual implementation of data-driven decision-making. But it’s important to also be aware of the dimensions of internal and external integration to get full performance. The different parts reinforce each other, and it’s not possible to compensate for one dimension with another”, says Jon Bokrantz.

In order to have correct knowledge on what current level of smart maintenance a company is at, Chalmers has developed the self-assessment tool Smart Maintenance Assessment (SMASh). SMASh has been produced in collaboration with the industry and is based on approximately 100 scientifically developed questions. Measurements from over 150 Swedish factories have clearly shown that those who achieve high levels of smart maintenance can improve their maintenance performance and productivity. The most high-performing maintenance operations have significantly higher levels of data-driven decision-making compared to other factories.

“The factories that succeed best with smart maintenace often already have clear processes that are reinforced with a good data. The data is measured and used with a clear connection to productivity rather than traditional maintenance indicators. There’s also a desire to experiment when it comes to testing and introducing new technology, but without using more complex tools than necessary. Smart maintenance is not about throwing out everything old replacing it with data and push on a button. It’s important, as with all other activities, to work systematically with planning, execution and evaluation”, says Anders Skoogh.

Generic tips to be successful with Smart Maintenance

Generic tips to be successful with data-driven decision-making:

Data-driven decision-making consists of making maintenance decisions based on data from production equipment.

• Implement and use a computerized maintenance management system where maintenance activities are planned, registered, and followed up.
• Identify the data sources that are already collected in the factory today together with mapping important decisions within your maintenance organization. Decide which decisions that should become more data-driven, and thereafter start to analyze the data sources that are needed to make these decisions.
• Establish teams and working procedures for collection, quality assurance, and analysis of data.
  Start pilot projects within Artificial Intelligence and Machine Learning to understand how future technologies can create value in the organization.
• Combine different data sources from the entire factory, develop algorithms and decision-support, and drive the need for data-driven decision-making processes on a daily basis.

Generic tips to be successful with human capital resource:

Human capital resource consist of the knowledge, skills, abilities and other charachtersitics of the maintenance employees.

• Validate and develop basic maintenance competence, e.g. via www.svenskindustrivalidering.se
• Develop the internal collaboration within the maintenance team, e.g. through close collaboration between reactive and preventive personnel, planners and repairers, and electric and mechanical staff.
• Analyze the current competences and future need for digital skills within the maintenance team (e.g. analytics- and IT-skills). Develop a strategi för competence development and recruitment (e.g. specialist staff for data analytics).
• Map the maintenance organization’s total competence requirements and identify which competence areas that needs to be developed in-house, in partnership together with other factories or partners, or externally sources from suppliers.
• Stimulate individual competence development using e.g. podcasts, online courses, or courses via Chalmers.

Generic tips to be successful with internal integration:

Internal integration is when maintenance is a part of a unified whole within the factory.

• Develop the relationship to other functions and departments such as production, purchasing, and quality. Establish shared goals and work procedures as well as create specific roles that are responsible for cross-functional collaboration.
• Establish routines for the internal collaboration within the factory, e.g. in the form of morning meetings, cross-functional root cause analyses, and collaborative improvement teams.
• Create joint key performance indicators in the factory to ensure that the organization is monitored in a prioritized and fact-based way. Update these indicators continuously by means of data analysis.
• Share data and information sources between departments and establish joint decision-making, e.g. by integration of information systems used in maintenance and production.
• Establish shared values in the factory that creates incentives and motivation to drive strategic development together.

Generic tips to be successful with external integration:

External integration is when maintenance is a part of a unified whole outside the factory.

• Engage in maintenance networks, seminars, research, and fairs where you actively share knowledge and experiences with other companies.
• Establish closer contact with key suppliers that can provide expertise to analyze, improve, and execute maintenance actions.
• Continously evaluate your maintenance organization using benchmarking.
• Establish joint information sharing with strategically important partners, e.g. sharing cost information, spare parts, scheduling, root cause analyses, and machine data.
• Connect machines and equipment to suppliers to enable e.g. online monitoring, remote support and real-time data sharing.