Predictive maintenance brings together science, business and technology in a way that can massively improve the functioning of a distribution operation.
If one part of the distribution system fails, it can bring the entire warehouse to a halt. Productivity takes a sharp dive and means customers don’t receive their goods. The risk to the business is enormous.
But with predictive maintenance, a warehouse can have greater confidence that its machinery won’t break down.
What is Predictive Maintenance?
With predictive maintenance, data from machine sensors is analysed to check how the machinery is functioning. Then, by applying algorithmic logic, it can be determined when it will need to be serviced.
This anticipates any breakdowns, by predicting when a piece of machinery is likely to stop functioning, or to have issues. Then, a warehouse can devise a custom plan for the maintenance of the equipment. Implementing this plan ensures that the maintenance is carried out before any breakdown.
Predictive maintenance differs from the other types of maintenance.
With planned or preventative maintenance, for example, the maintenance is carried out to a fixed schedule. The maintenance can be carried out at a convenient time – out of business hours, for example, and usually the costs are the most reasonable of all the types of maintenance, because it can be pre-scheduled. However, as it can come too early – way before a likely breakdown – the maintenance may be entirely unnecessary, but the warehouse still bears the costs of it anyway.
Condition-based maintenance is similar to preventative maintenance, but it is based more on usage. For example, where preventative maintenance might be carrie out every certain number of months, condition-based maintenance will be applied according to how much a certain piece of machinery has been used. In the warehouse, conveyors may be in use 100% of the working time, but other material handling equipment may either be inherently more reliable, or may only be used 50% of the working day. Here therefore, maintenance can be planned based on certain conditions of usage. Again though, this is a preventative approach, and could be undertaken before its needed.
Then there’s reactive or corrective maintenance. This type of maintenance always comes too late. Its very name denotes that it comes after the fault has been discovered. Not only can it be harder to find someone at short notice with the availability to visit and repair your equipment, but it also often means that it’s more expensive too. It’s like calling out a plumber when your shower breaks. You need it back working again as soon as possible, but you’ll struggle to find someone quickly, and when you do, you’ll pay a premium for the service.
How does Predictive Maintenance work?
Predictive maintenance systems vary. But in essence, there are four main steps:
- Machine sensors send performance data to the central system
- The data is scrutinised by applying advanced analytic and visualisation techniques
- Analysts determine the likelihood and future time of equipment failures
- Maintenance is scheduled at the correct time
For the system to become most effective, lots of data is needed over a period of time. Analysis of a number of failures and the preceding data is what helps to inform similar future events.
What are the challenges of Predictive Maintenance?
One of the most challenging aspects of predictive maintenance is obtaining the data. Not all materials handling equipment can yet supply data, nor can be retrofitted with sensors that will provide the data needed.
And then there’s the costs. Significant upfront investment is needed to establish the right processes, invest in sensors for the machinery and implement the IT infrastructure and systems needed to carry out the analysis.
Equally, the data needs to be interpreted by a skilled data analyst. A warehouse needs to find someone with the expert knowledge that is required to set up and run a predictive maintenance system.
How can predictive maintenance help?
According to Deloitte, “On average, predictive maintenance increases productivity by 25%, reduces breakdowns by 70% and lowers maintenance costs by 25%.”
And if successfully implemented and running optimally, it could conceivably assure a 100% functioning of the warehouse.
The predictive maintenance increases the overall equipment effectiveness and therefore reduces or completely prevents breakdowns. In turn, this minimises or eliminates downtime in the warehouse, which keeps productivity high.
Also, the warehouse knows which parts are required in advance and these can be ordered and made available in time for the planned maintenance.
Is predictive maintenance the future in warehousing?
Predictive maintenance is already in use in manufacturing, facilities management, and telecoms networks. And solutions have been exhibited over the past few years at a number of supply chain events worldwide.
For any facility that depends on the reliability of its assets, then predictive maintenance is an advantage. For warehouses with mission-critical equipment that need to minimise downtime and maximise equipment efficiency, then it seems it’s certainly going to be the future.