Being a significant expense of any manufacturing company (commonly between 10% to 15% of total operating costs), maintenance has long been the focus of production efficiency efforts.

Industry 4.0 technologies such as digital twin and artificial intelligence are proving that even the best results from traditional maintenance methods can be improved upon by at least 30%.

That figure is a serious game changer for any manufacturer.

To achieve maintenance efficiency, a number of issues should be addressed:

  • In the case of a specific machine’s failure, what is its impact on the factory/plant’s throughput?
  • In the case of multiple machine failures, which maintenance job should be executed first?
  • What is the effect of the various failure types on production throughput and quality?
  • Which maintenance activities are possible to perform without affecting the production schedule?
  • What’s the most efficient use of factory/plant resources – labor, materials and equipment – for performing maintenance?

In this post, we’ll look at how Intelligent Maintenance Systems help answer these questions, and in turn, improve maintenance efficiency.


So, what is an Intelligent Maintenance System?

“Intelligent maintenance system” is an umbrella term for a number of approaches that share a common goal: to improve the efficiency of maintenance activities through the use of digital technologies.

An intelligent maintenance system (IMS) uses sensors, hardware processors, cloud applications and advanced analytics to improve the performance of maintenance for a machine, production line or manufacturing facility.


How manufacturing facilities benefit from utilizing an IMS

The challenge in answering the questions above lies in the fact that they all depend on a large number of interlinked parameters; parameters that change over time, both in the short and long-term.

Fluctuations in environmental factors, the quality of raw materials, asset health status, workforce, market demand, and many others affect the required rate and type of maintenance.

So, how can manufacturers gain control over ever-changing operational environments?

The answer: by being able to predict.

One of Industry 4.0’s most powerful use cases is predictive maintenance which leverages data captured from sensors, PLCs, data historians, ERPs, MESs etc. to form failure predictions.

Machine learning and other AI algorithms such as artificial neural networks are used to process this data constantly. The algorithms search for correlations that can help determine the root cause of recurring problems that lead to unplanned downtime.

artifical neural network schematic
Schematic of an artificial neural network. ANNs are used to discover causal correlations between root causes and failures.

The ROI of IMS

An IMS with predictive maintenance capabilities will autonomously alert relevant personnel about issues and only recommend maintenance activities when necessary.

In this way, maintenance efficiency is significantly improved, offering manufacturers a number of benefits that positively affect the bottom line:

Lower maintenance costs – Repairs are performed when needed instead of according to a predetermined schedule (which in many cases leads to redundant checks/maintenance activities).

Increased uptime – With IMS, downtime can be scheduled, and as a result is usually much shorter than what’s needed for reactive repairs.

Reduced labor costs – Maintenance teams are smaller since tasks are planned beforehand.

Lower equipment costs – Maintenance focuses on the problematic components only. This prevents wear and tear to surrounding parts during the repair and prevents unnecessary replacements.

Lower inventory expenses – Since problems are predicted, orders are made only for materials and components that will be needed in the near future.

Lower chance of secondary damage – Because problems are detected early on, they can be dealt with before more extensive damage is done to equipment.

Increase in Remaining Useful Life (RUL) – The root cause of issues is pinpointed making the need for disassembly less frequent.

Quality 4.0 – By improving asset health, deviations in performance become far less frequent, leading to consistently high levels of output quality.


Maintenance doesn’t have to be a sore point

By deploying an Intelligent Maintenance System, today’s manufacturers have the opportunity to overcome maintenance challenges and gain control over complex production issues.


Contact us to find out how your operation can reduce unplanned downtime and prevent quality deviations using intelligent maintenance.

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