Production Outage (Interruption) Durations Can Be Minimized With Predictive Maintenance

Unplanned Outage Duration

As per the report of market research firm Vanson Bourne, 82% of manufacturers experience at least one unplanned machine outage every year. According to market researches, production interruptions are quite common and cost producers extremely much. Today, the elimination of these outages; as going beyond the old maintenance methods, becomes possible with the application of predictive maintenance solutions.

Although unplanned outage of machines has quite a disadvantage on income and productivity, the reason why it is so common is due to the two traditional methods that facilities use as a machine maintenance tool.

Reactive and Preventive Maintenance;

Traditional approaches related to machine maintenance are not sufficient to limit or eliminate unplanned downtime. When your technicians notice signs of machine problems (such as poor quality printouts or machines completely broken), they will reactively investigate the problem. Seeking a solution with a reactive approach will not be correct and sufficient; because once your workers get that a problem exists, your machines have already had the problem and your product has already been affected. Your unsuccessful or under-performing machines, causing outage by stopping the production lines, can cause a serious decrease in your income and production rate.

The preventive approach is a second traditional maintenance method and is a more precautionary approach. Maintenance technicians aim to catch problems earlier by performing machine maintenance on a scheduled basis and in a programmed manner. Although it is a more successful approach compared to the reactive approach, the success rate is still low. Because with this kind of approach, a malfunction can only be prevented before it happens if it coincides with the scheduled maintenance time. For example, if a machine begins to underperform shortly after the scheduled maintenance, it may continue to underperform or even break down until its next scheduled maintenance.

Both maintenance methods have traditionally focused on responding to signs of machine’s poor performance or malfunction. As most factories use one or both of these methods for machine maintenance, the vast majority still suffer from constant unplanned outages. Factories should focus on detecting potential problems before they occur, rather than trying to recover machine health with these methods.

Predictive Maintenance

‘Predictive Maintenance’ provides your technicians with advanced alerts to resolve issues before unplanned outages occur.

With the advent of smart sensors, factories were for the first time able to take a completely proactive approach to machine maintenance. Machine health data is monitored in real time with sensors attached to the machines, then this data is sent to an industrial internet of things platform for analysis and predictions. Thus, the platform can send automatic and real-time alerts to technicians.

New generation technology, rather than traditional methods, promises solutions where you can monitor the health of your machines and significantly reduce unplanned downtimes. How does it work?

1) Optimize The Repair-Time

An unexpected outage (interruption) can bring production to a standstill, as well as lead to huge cost losses. Your technicians need to diagnose and fix outages as quickly as possible. However, because the work is reactive, there is no way of knowing how long diagnostics and repairs will take. In planned machine downtimes, manufacturers can prepare for outages in advance. Predictive maintenance tools monitor machine health data to distinguish whether a machine needs maintenance, so you can plan outages and focus only on equipment that needs attention. Technicians can come up with early and clear solutions to minimize negative impacts on production. Once these proactive interventions become habitual, unplanned outages will also become extremely rare.

2) Get Maximum Benefit From Your Planned Downtimes

For example, let’s consider a factory with 100 machines. Of these machines, 3 are on the verge of failure, 15 are in critical condition, 20 are deteriorating and the rest are in good condition. This company, which has 3 maintenance personnel, has six scheduled maintenances in the next six months, and the first four of these maintenances consist of two-hour maintenance and the remaining two consist of eight-hour maintenance. How can this team provide maximum benefit in maintenance planning at specified times?

Machine health data reveal which equipment requires urgent maintenance and which can be delayed until a little later. It also helps to identify where, when, and how a machine needs repair so technicians can implement the most effective solution as soon as possible.

3) Be Prepared

When you can optimize every maintenance opportunity in your factories, you can begin to prepare for maintenance in the long run. In other words, instead of waiting for the next failure, you can reduce your unplanned machine outages to near zero with predictive maintenance. You can make individual plans for each machine, start ordering spare parts early, and organize staff according to skill sets. With enough fine-tuning, your technicians will know exactly what to do so that scheduled maintenance will proceed systematically.

In the past, unplanned outages were thought of as expensive disasters waiting to happen. But that was before the predictive maintenance period.