According to a recent survey conducted by Oneserve in partnership with British manufacturers, downtime costs Britain’s manufacturers more than £180 billion every year. This is an extraordinary figure, but additional unexpected costs hit businesses in high volume low margin sectors hardest.
High volume, low margin manufacturing is a challenging business model that typically applies to fast moving consumer goods (FMCG) or food and beverage manufacturers, particularly the makers of private label or generic products. These sectors rely on maximising production volumes and minimising overheads. If volumes are below forecast or overheads are above, the manufacturer risks slipping margins or even running at a loss. Worse still, some retailers may impose fines on suppliers who fail to deliver on time.
There are tough decisions for manufacturers to make about how much cost and effort should be assigned to maintain a plant at a level where breakdowns will be sporadic enough to ensure volume targets are met. In the low margin high volume world, money spent on preventative maintenance may be seen as wasted, as there is no immediate benefit from the outlay. Even long-term benefits are difficult to attribute to earlier spend, since the benefit is typically a reduction in breakdowns, which can be difficult to monitor with no baseline.
As an alternative to preventative maintenance, plant operators might opt for corrective or reactive maintenance, which means waiting for something to fail, then trying to fix it as quickly as possible. The downside of this method is that the maintenance team could be faced with the difficult and time-consuming task of getting production running again. With thousands of possible failure scenarios, there is a risk that the information, spare parts, tools or knowledge may not be on hand to enable the machine to be fixed quickly.
In most cases, manufacturers use a combination of preventative and reactive maintenance. However, reactive maintenance will always take priority, meaning that preventative maintenance may not take place when a plant is experiencing regular breakdowns. This can lead to the situation becoming even worse.
At its most basic, preventative maintenance consists of activities performed on a regular basis to lessen the likelihood of equipment failing. During these activities parts will often be replaced based upon statistics such as average lifespan and known likelihood of failure, rather than their actual wear.
Regular preventative maintenance does increase asset lifespan and reliability, but it can also be costly in terms of parts and scheduled downtime. Without maximising wear of parts there is no guarantee that the valuable funds could not be better spent in a different part of the plant.
Another option is predictive maintenance, a specific form of preventative maintenance. In predictive maintenance, a maintenance regime is determined by the actual condition of equipment, rather than relying on expected statistics, such as average lifespan of parts.
By using sensors to monitor equipment, predictive maintenance can accurately predict failure before it occurs. For example, if a sensor detects a motor is running at a higher temperature than usual, lubrication and cooling systems, such as fans, can be checked and changed, even if a replacement wasn’t yet scheduled. Likewise, if the operational conditions are more favourable, maintenance intervention can be delayed in order to maximise the lifetime of parts.
Using the concepts of Industry 4.0 and the Industrial Internet of Things (IIoT), when connected to the plant networks, data produced by sensors can be transmitted to a centralised location or the cloud, where it can be stored and analysed to highlight trends, reducing the chance of future breakdowns.
Risk based maintenance
Manufacturers looking to benefit from predictive maintenance can also carry out risk based maintenance. For many businesses operating under high volume low margin parameters, risk based maintenance can be the best compromise as it allows for significant reduction in breakdown costs, without the need for the high upfront costs associated with predictive maintenance.
Risk based maintenance integrates analysis, measurements and periodic tests, in addition to using predictive lifecycle statistics. During risk based maintenance, a plant is expertly assessed, taking into account each of these parameters, before an appropriate maintenance programme is decided on. This includes decisions such as what maintenance tasks are urgent or crucial, based on the risk it poses of causing downtime.
A risk based strategy also allows for maintenance to be carefully scheduled, which could mean part of the plant can continue to operate while planned downtime is carried out in another area.
Information used to plan risk-based maintenance must be taken in context with the environment, operation and process condition of the equipment in the system. For example, the same motor will last longer when used intermittently in an automotive parts production plant than when used continuously and subjected to washdowns in a food processing plant.
All equipment that is deemed to be high risk by displaying abnormal values when undergoing periodic tests, or equipment that is likely to become obsolete, will be replaced or refurbished during risk based maintenance. This can extend equipment life span and guarantee high levels of reliability, safety and efficiency, without the expense of condition based predictive maintenance.
Risk management assessments are easy to carry out and can allow plant managers to spot problems before they occur and put solutions in place. Boulting Technology’s no obligation online control system risk management tool considers factors such as obsolete parts, equipment lifecycle and efficiency to produce a traffic light system and make recommendations on how plant managers can reduce the risk of their system breaking down.
Regardless of the type of maintenance being carried out, there are a few considerations to be aware of throughout a product’s lifespan and planned for accordingly. These include planning for obsolescence, even when the product is new, and ensuring each addition to the manufacturing line does not compromise the cyber security of the plant.
It also helps ensure that new vulnerabilities are not opened up as a result of a lack of maintenance.
By Phil Black