Shaping the future of obsolescence management

“The only way to predict the future is to have the power to shape the future,” said the American philosopher, Eric Hoffer. However, this is becoming more difficult for manufacturers due to the growing problem of obsolete equipment, which is machinery that is no longer produced by the original equipment manufacturer and whose spare parts can be hard to find.

According to a survey by Atomik Research on behalf of Shire Leasing, 52 per cent of manufacturing employees said that outdated equipment regularly hindered their work. Obsolete equipment creates issues for all kinds of manufacturing professionals, at all levels, from business owners to operators and maintenance engineers. A global study by GE Digital found that 82 per cent of businesses had problems with unplanned downtime, costing an average of $260,000 an hour across the 450 companies surveyed.

Replacing obsolete assets can be difficult. Sourcing a like-for-like replacement part, right down to the necessary serial number, might not be possible if the equipment is no longer manufactured. On the other hand, replacing an obsolete asset with a newer model might be costly and disruptive, and isn’t necessarily the best option.

Repairs can be cheaper than investing in a replacement — depending on the size, power or type of a machine — yet this approach is also problematic. Once we factor in disruptive factors like production stoppages, lost time and resources and consequences elsewhere in the supply chain, it’s estimated that the true cost of a machine breakdown can be from four to 15 times the maintenance costs.

Spot and manage issues

So, what can manufacturers do to mitigate the consequences of machine obsolescence? An idea can be found in another study by GE, which found that only 24 per cent of managers described their maintenance approach as predictive.

This suggests many production environments rely on preventative maintenance strategies, rather than predictive, which means assets are replaced and maintained according to a predetermined schedule. Problems here include that faults may worsen or lead to failures between checks, leading to a reactive maintenance approach where faults aren’t addressed until it’s too late.

Nevertheless, GE’s study points us towards a solution: predictive maintenance using digital technologies that collect, monitor and analyse data generated by industrial assets.

Not only does predictive maintenance become possible through Industry 4.0, technologies like sensors can help diagnose problems faster than a human engineer would. Moreover, these systems can help manufacturers predictively spot and manage issues of obsolescence in ageing plant equipment. Let’s examine how.

Predict the future

According to Technavio, the industrial predictive maintenance market in APAC is expected to grow at a compound annual growth rate of more than 34 per cent between 2021 and 2026. This is thanks largely to continued advancements with the Industrial Internet of Things (IIoT), artificial intelligence (AI) and big data.

Industry 4.0 sensors attached to equipment at the device level can support real-time adjustments by gathering data, which is fed back to a plant’s supervisory control and data acquisition (SCADA) and manufacturing execution systems (MESs) and then processed, analysed and visualised by engineers in real-time.

With this data, plant managers can perform the first steps of an effective obsolescence management strategy. These are system assessment, resource planning and risk analysis. These steps should take into account the lifespan of all equipment and components in the production plant. In other words, plant managers should know how old everything is and flag any signs of damage that could impact the equipment’s performance. The objective is to replace obsolete parts as they age, and before they impact productivity or cause downtime.

The next two stages in an obsolescence management strategy are to create a database, and review and update this information. Data on obsolescence risks throughout a plant should be easy-to-access, and it can be as simple as creating a spreadsheet which highlights areas of concern on the shop floor. The database can include suggestions on how to proceed in managing the risk.

This leads to the final two steps in our obsolescence management strategy: finding the right supplier, and shopping and stocking parts. The database should contain the contact information of a trustworthy supplier, which specialises in obsolete automation parts and will be ready to assist manufacturers when legacy components need to be replaced.

Above all, it should be remembered that obsolescence management is an ongoing process. This is where the automated real-time capabilities of Industry 4.0 and sensors give plant managers the power to shape the future, to quote Eric Hoffer. By helping human workers preventively maintain obsolete equipment throughout their plant, digitalised obsolescence management gives them the power to predict the future.