A comprehensive strategy to mitigate unplanned downtime and achieve peak productivity
Machine failure can be caused by multiple reasons, ranging from ineffective maintenance to repair quality and human errors. By implementing a well-planned strategy, most of these issues can be mitigated, helping to avoid machine downtime and unlock unprecedented efficiency levels.
Reducing or avoiding machine downtime is one of the key objectives in asset-intensive businesses. This is not without a reason: the cost of machine downtime has been rising, and has shot up by 50% over the last 2 years. In some sectors, the cost of unplanned downtime is $2m/hr, and Fortune 500 industrials lose $1.5tn/year (equalling 11% of their annual revenues) due to the same reason.[1]
However, with effective organizational management and use of digital technologies, it is now possible to eliminate unplanned downtime altogether. In this article, take a look at some of the most effective ways to avoid machine downtime, and maximizing operational efficiency.
Failure is not an exception, but a rule
In any asset-intensive business, machine failure is inevitable. It is unplanned failures and outages that result in these steep costs. Therefore, one of the key steps to reducing downtime, is to accept the fact that failures and outages will happen.
Planning for failure
There are multiple ways to plan for machine failure. One way is to prepare for a corrective action beforehand – in other words, have spares in your inventory, or conduct preemptive repairs. Another way is to make calculated estimates about when a failure could occur. A third strategy could be to reduce the time it takes to recover a machine after failure.
Such strategies help you address the various factors that lengthen the span of each incident of outage.
Six actionable steps to reduce machine downtime
Take a look at some of the actionable steps to mitigate unplanned machine downtimes.
#1. Understand the cost of machine downtime
Unplanned downtime incurs multi-dimensional costs to firms – including revenue losses, and costs of wages of affected employees who can’t work, repair technicians, emergency spare part sourcing, and contractual compensations.
Adding up these costs will give you a rough estimate of how unplanned downtime affects your firm – and this can help you gain buy-in from senior leadership to address its root causes.
#2. Install sensors to monitor and predict outages
Reducing cost of Internet of Things (IoT) sensors has opened up a new way to monitor machine condition remotely. Temperature, pressure, proximity, and humidity sensors are now cheaply available – these can be installed on equipment, and connected to a wireless network. IoT sensors are an effective means of monitoring legacy equipment that offers limited SCADA capabilities.
The data emitted by these sensors can be collated on remote computers, and this data can be monitored by plant operators. A rapidly heating piece of equipment or abnormal pressure serves as clues that can help operators spot an oncoming fault in a machine. This can help them prepare for corrective actions in time.
#3. Codify the expertise of plant operators with AI
Experienced plant operators may be able to manually monitor sensor data from machines, but this approach is not without limitations. Firstly, 24×7 manual monitoring may not be viable for always-on plants. Secondly, plant operators may not be able to make sense of continuous streams of data from multiple machine systems.
An effective approach is to train advanced algorithms to spot anomalies in data streams from IoT sensors. These algorithms can monitor sensor data 24×7, and can even predict a failure before it can happen. Such algorithms constitute artificially intelligent (AI) systems that are leveraged to operationalize predictive maintenance strategies.
#4. Incorporate inventory considerations into your maintenance schedules
Evidence suggests that despite fewer incidents of unplanned downtime, recovery times are growing.[2] One of the reasons for this, is growing lead times of some parts due to changing supply chain dynamics. The underlying reasons differ by the sectors – some are facing supplier disruptions due to geopolitical tensions, whereas others are experiencing longer wait times due to semiconductor shortage.
When you prepare preventive or predictive maintenance schedules, it is crucial to factor lead times, and maintain your inventories accordingly. Emergency sourcing of equipment, or uncertain delays due to unavailability of spares will only raise the cost of unplanned downtime to your business.
#5. Focus on improving the time-to-resolve
When a machine failure does happen, technicians can often take hours and days to understand the root cause of the failure. This is especially true for complex systems like oil rigs, rotary kilns, and hydraulic and wind turbines. In some cases, it becomes difficult to assess the condition of an equipment because some of its parts are inaccessible.
In other words, even if the operator knows that the equipment is likely to fail within a couple of weeks, corrective actions will introduce unplanned downtime into plant operations. That’s why, it is equally necessary to know what the likely cause of failure will be.
Today, machine learning systems can predict the failure mode for a piece of equipment with considerable accuracy, thus minimizing downtime in production, This can help technicians conduct repairs and maintenance activities within smaller timeframes, and with fewer trips to the site / equipment. This reduction in MTTR significantly reduces both planned and unplanned downtime, while improving productivity levels.
#6. Implement a predictive maintenance solution for your plant
A predictive maintenance solution is more than just an algorithm or a visualization dashboard. It not only brings industry-leading ML models that are purpose built to anticipate failure modes for specific equipment, but also codifies knowledge and best practices of hundreds of expert plant operators.
In addition, they can also integrate with other enterprise technology like asset management systems, ERP, and SCADA to transform maintenance workflows end-to-end. Therefore, they help you transform your equipment maintenance strategy inside-out, and can bring unplanned downtime to a minimum.
What next?
Unplanned downtime contributes to massive revenue losses each year. Given that some industries face 800 hours of equipment downtime annually, mitigating unplanned downtime can have a significant impact on the bottomline.[3]
While machine failure may be inevitable, unplanned downtime isn’t. With a calculated strategy that makes use of advanced AI, unplanned machine downtime can not only be minimized, it can be eliminated altogether.
See how predictive maintenance solutions like UptimeAI can effectively reduce machine downtime – contact us now for a free demo.
[1] https://assets.new.siemens.com/siemens/assets/api/uuid:3d606495-dbe0-43e4-80b1-d04e27ada920/dics-b10153-00-7600truecostofdowntime2022-144.pdf
[2] https://assets.new.siemens.com/siemens/assets/api/uuid:3d606495-dbe0-43e4-80b1-d04e27ada920/dics-b10153-00-7600truecostofdowntime2022-144.pdf
[3] https://www.forbes.com/sites/forbestechcouncil/2022/02/22/unplanned-downtime-costs-more-than-you-think/?sh=5468da9636f7