Maintenance data at the core of data-driven maintenance

The data accumulated in the maintenance system can be trusted when the system's usage rate is high and reporting is systematic. This requires that the system is central to operations and that its usage is at a good level.

How is maintenance data refined into additional value for business operations and decision-making?

Data-driven maintenance: World-class maintenance is based on reliable and up-to-date information.

Reliable and up-to-date maintenance data is the backbone of a maintenance organization’s operations. Data is utilized in daily work to ensure that planned tasks can be carried out both efficiently and with high quality.

The historical data accumulated in the maintenance system is also used for long-term planning. Over time, quality maintenance data helps identify operational bottlenecks and access information such as the lifecycle costs of equipment. Quality data, therefore, enables a more precise overall picture of maintenance operations.

Read: What Is Quality Maintenance Data?

What challenges are associated with data-driven maintenance management?

When we talk about maintenance data, we often refer to the information generated from daily maintenance activities, such as entries made by personnel in the maintenance system regarding machine faults, repairs, and services. This data provides organizations with valuable insights into the efficiency and performance of their operations and forms a solid foundation for decision-making and operational development.

Maintenance data can be trusted when the system’s usage rate is high, and reporting is systematic. This requires that the system is central to operations and that its usage is at a good level. Ensuring this is always the responsibility of management.

Features of the Novi maintenance system

Not enough work Is logged into the maintenance system

Reliable conclusions and decisions can only be made if a sufficient amount of work is logged into the system. For example, if only 60% of maintenance work is recorded in the system, nearly half of the situations are left out of the analysis. The data accumulated in the system no longer represents reality, and decisions are not based on a realistic situation.

The entries made in the maintenance system are not of sufficient quality

The description of the work and the actions taken must be recorded in the maintenance system in sufficient detail to be beneficial. A mere event log does not provide added value for decision-making, as it does not convey the nature of the problem, its causes, or its consequences.

Accumulated data is not utilized sufficiently

Entries made in the maintenance system alone are not enough for a continuous improvement process. The collected data must be used in such a way that it translates into concrete actions. If collecting the data is not seen to provide concrete benefits, the motivation to make entries will diminish.

Insufficient time is allocated for data analysis

Data analysis and the subsequent operational development often get overshadowed by daily tasks. Therefore, it is important that the system supports reporting so that problem areas and bottlenecks can be quickly and easily addressed. A visual presentation helps to understand the overall picture better and faster.

Towards even more efficient maintenance with artificial intelligence

As technology advances, the amount of data generated from production processes continues to grow. For example, the increase in various measurement points produces data that can be effectively utilized in maintenance planning.

However, the vast amount of information makes data analysis challenging, and in the future, various AI solutions will help manage the data load. Artificial intelligence will identify process deviations and suggest necessary maintenance tasks. AI will also play a significant role in the planning and optimization of plant maintenance. Novi’s modern technology ensures that users can fully leverage the opportunities offered in the future.

Artificial intelligence and machine learning bring efficiency to production and the supply chain.

Novi BI transforms maintenance data into truly valuable information

Novi BI is an additional service for Novi’s cloud service customers. It integrates intelligent Business Intelligence reports into the maintenance system, providing an overview of the state of maintenance. With BI, a separate data warehouse can be created, or reporting features can be embedded directly into Novi.

In addition to clearly visualized ready-made report templates, Novi BI also offers customized reports tailored to your company’s needs. Ready-made reports are available on themes such as:

  • Fault Analysis
  • Maintenance KPIs
  • Cost Tracking
  • Daily Maintenance Management

Read more >>

Read more about developing maintenance:

Novi by Pinja maintenance system

The Novi maintenance system is a tool for managing and developing preventive maintenance. It is designed to support you in maintenance management and development, as well as in digital transformation. With the system, you ensure high utilization rates for your production equipment, control costs, and create a safe working environment for your organization.

Maintenance expert services

There are various tools and methods available for creating a maintenance development plan that help assess the current state and build a path toward the target state. Choosing an expert as a partner in development work ensures success now and in the future.

Integration

The need for comprehensive integrations is constantly growing. A well-constructed system setup significantly eases daily work for the user, and the boundaries between the systems are barely noticeable.

250+ customers

500+ or use case

30+ in different countries

20+ in different languages

10 000+ users

Novi allows us to allocate and track maintenance costs. With the system, we have been able to develop equipment investments and preventive maintenance, which in turn has led to improved operational reliability of our

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In addition to the scope of work performed by our maintenance personnel, we monitor the hours used and machine downtime. We also utilize Novi's spare parts features to track common spare parts across all our operating l

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At Helsinki-Vantaa, we focus on monitoring key metrics such as MDT, MTBF, MWT, and machine utilization rates. Monitoring KPIs is conveniently done directly in Novi, but in addition to monitoring, the system also identifies areas for improvement.

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Pinja's way of modeling and assembling development ideas into a scheduled and implementable format is excellent. The operating model has been an effortless and effective way for us to collaborate.

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One significant advantage of Novi is the support it provides for lifecycle management of maintenance assets. Our goal is to optimize the value and performance of assets throughout their lifecycle. This approach promotes efficient resource use.

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We reviewed several alternative systems and ultimately chose Novi for its flexibility, mobility, and customizability.

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Contact our experts

The foundation of our maintenance system deliveries is always a deep understanding of the client’s maintenance processes and pain points. Our experts are specialists in maintenance development and bring diverse expertise to projects to support the client.

Novi support

010 347 2177