Asset management: Is break-fix maintenance a thing of the past?

Jun 04, 2024
  • discrete manufacturing
  • engineering & projects
  • professional services
  • Microsoft

The manufacturing sector is one of the UK’s largest industries, with 9.3% of total UK economic output being produced by manufacturing businesses.  

And with machinery essential for the production of goods and services, the UK production total for the manufacture of machinery and equipment sat at over £3.5 million as of March 2024. 

As industry professionals know all too well, machinery requires constant maintenance. When assets are not maintained to a high standard or are not regularly serviced, excessive downtime can result, causing negative impacts on the quality, quantity, and profitability of the production process, as well as customer satisfaction and loyalty.  

Historically, manufacturers have adopted reactive, or break-fix, maintenance strategies, but in the era of the technology revolution, is the time for change overdue? 

Let’s take a look at the different asset management maintenance strategies adopted today:  

Reactive maintenance 

As mentioned above, reactive maintenance is another term for break-fix maintenance and refers to the repair or replacement of machinery when things go wrong. This means that no preventive actions are taken to avoid breakdowns or to preserve the optimal condition of the machines.  

Whilst reactive maintenance can be suitable for non-critical assets that have low repair costs and low impact on safety and productivity, for more important assets or higher priced repairs, reactive maintenance can lead to higher downtime, lower efficiency, reduced lifespan, and increased risk of accidents. Therefore, most manufacturers today prefer to adopt proactive maintenance strategies that can prevent failures and optimise performance… 

Preventive maintenance

Preventive maintenance is the simplest form of proactive maintenance, whereby repairs and services are generally based on a fixed schedule.  

Such a schedule can be either time or usage-based, for example, servicing the machine either every six months or after every 1,000 products produced. The planning and schedules of the maintenance are typically based on either the manufacturer's recommendations, historical data, or industry standards. 

Furthermore, performing regular inspections and tests to detect any signs of wear and tear, malfunction, or deviation from the expected performance is also a form of preventive maintenance.  

Preventive maintenance can decrease downtime and reduce unnecessary product replacement expenditure when compared to reactive maintenance, as regular services can help prolong the lifecycle of assets. 

Conditional maintenance

Utilising Internet of Things (IoT) technology, manufacturers can continuously monitor and assess operational health with triggered alerts that indicate maintenance requirements. For example, sensors can detect when certain events have happened, such as an increase in temperature or a drop in output. 

This is called conditional maintenance, which aims to prevent failures or defects before they occur by detecting and correcting any anomalies or deviations from the normal or expected state of the machine or equipment.  

Conditional maintenance can reduce unnecessary maintenance costs and improve the reliability and availability of the machines or equipment. It is more efficient than preventive maintenance as it bases servicing on the actual condition or performance of the machine or equipment rather than the assumed condition or performance, meaning that maintenance actions are only performed when needed, avoiding wasting resources and time on unnecessary or ineffective maintenance actions. 

Predictive maintenance

With the significant increase in the use of artificial intelligence (AI) across UK businesses in recent years, the manufacturing industry has certainly embraced the revolutionary technology.  

Advancing one step further towards full efficiency, predictive maintenance is a type of maintenance strategy that uses AI to make predictions on when certain actions, such as an increase in temperature or a drop in output as noted in the conditional maintenance section above, are likely to happen.  

By analysing data from sensors, historical records, and other sources, predictive maintenance aims to anticipate potential failures or malfunctions before they happen. Essentially, AI technology helps spot patterns to determine what causes such actions, so that the problem can be rectified before the action even occurs. 

The next move for manufacturers

In the wake of a post-COVID, post-Brexit UK, the manufacturing industry certainly has to contend with mass unpredictability. And with the need for resilience pressing more so than ever before, wasted downtime and lost profits simply won’t do.  

The answer is simple – efficiency is key to survival. 

Those who continue to rely on a break-fix strategy for their asset management risk the quality, quantity, and profitability of their processes. If they want to ensure optimal performance and avoid costly downtime to improve quality, save costs, and extend the lifespan of their assets, they must adopt a proactive strategy. 


With Microsoft Dynamics 365 Finance and Supply Chain, manufacturers can benefit from out-of-the-box asset management functionality. As a core module within D365, asset management allows businesses to monitor, maintain, and optimise their physical assets throughout their lifecycle. 

It helps them to plan and execute preventive, conditional, and predictive maintenance activities, track asset usage and performance, schedule work orders and inspections, manage spare parts and inventory, and comply with industry standards and regulations.  

Asset management also integrates with other modules in D365, such as production control, finance, and project management, to provide a comprehensive view of the costs and benefits of asset ownership and utilisation.

To find out how D365 can help your business, get in touch with our experts today.

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