Senseye has published a groundbreaking new report, The True Cost of Downtime, investigating the impact of machine failure and unplanned downtime at the world’s largest manufacturers.
Alexander Hill, Chief Global Strategist at Senseye, says, “unplanned downtime is the curse of the industrial sector. When expensive production lines and machinery fall silent, organizations stop earning, and those investments start costing rather than making money. The costs can spiral to well over $100,000 per hour for large manufacturers in almost all industrial sectors."
"With this report, Senseye has started to answer crucial questions, such as the true cost of downtime for large industrial organizations and the kind of savings companies could make by using techniques such as predictive maintenance to help prevent breakdowns and reduce unplanned downtime.”
Our study has thrown up some genuinely eye-watering statistics. In this blog, we look into some of the specifics.
Fortune Global 500 (FG500) manufacturing and industrial firms are taking a nearly $1 trillion financial hit yearly due to unplanned downtime. These companies are losing 3.3 million hours of production time annually to machine failure, with the $864 billion economic impacts of these lost hours equivalent to 8% of annual revenues.
When production lines and machines fall silent, expensive plants start costing rather than making money. Still, this study reveals the actual cost of unscheduled downtime at large industrial organizations is staggering. Breaking the statistics down by facility or sector makes them no less startling.
On average, large plants lose 323 production hours a year or 27 hours a month to machine failure - that’s more than a day’s production. The average cost of each hour of unplanned downtime is lost revenue, financial penalties, idle staff time and restarting lines is $532,000.
This amounts to $172 million per plant annually.
Broken down by industry, it looks like this:
- The cost of unscheduled downtime is highest in the automotive sector, where the products manufactured are of high value and plants and production lines are often closely interconnected, meaning downtime has a knock-on effect
- Automotive plants lose 29 production hours per month, on average, at the cost of $1.3 million per hour costing them $557 billion a year and 414,800 hours a year - an estimated 20% of annual revenue. Reassuringly, 67% of professionals in this sector told us that Predictive Maintenance was now a strategic priority
The cost of downtime is highest for automotive manufacturers
|Cost of Downtime||Automotive||FMCG / CPG||Heavy Industry||Oil & Gas|
|Unplanned downtime hours per facility each month||29||25||23||32|
|Cost per hour of downtime||$1,343,400||$23,600||$187,500||$220,000|
|Annual cost per facility||$468 million||$7 million||$52 million||$84 million|
|Estimated cost to Fortune Global 500 constituents||$557 billion||$35 billion||$225 billion||$47 billion*|
|Cost of downtime as a percentage of revenue||20%||4%||18%||1%*|
- The average number of hours lost due to downtime is highest in the Oil & Gas sector: 32 hours per facility each month. This could be due to the safety-critical nature of the work: production stops at the first sign of a potential problem
- Shutdowns in the Oil & Gas sector cost each facility $220,000 per hour - amounting to $84 million per facility each year. In refineries alone, losses to FG500 companies cost an estimated $47 billion from 213,000 downtime hours each year
- Not surprisingly, given the safety-critical nature of production, 82% of those in the Oil & Gas sector said predictive maintenance was already a strategic objective, the most of any sector
- While mining, metals and other heavy-industrial plants lose the least number of production hours each month to machine failure (23 hours), the cost is exceptionally high
- Machine failures cost heavy-industrial companies $187,500 per hour, on average. This eats heavily into profits, equating to 1.2 million unplanned downtime hours a year - totalling $225 billion a year across the FG500
- 60% of heavy industrial companies have now made predictive maintenance a strategic priority
- The last sector we looked at in detail at was FMCG. Here manufacturers fared best of any sector, losing 25 hours a month to unplanned downtime at the cost of $23,600 per hour. Across the FG500, this amounts to 1.5 million hours and losses of $35 billion a year or 1% of revenue
- FMCG manufacturers had the highest uptake of condition-based maintenance, an essential first step toward Predictive Maintenance. 67% of manufacturers in this sector told Senseye they approached maintenance this way in at least some of their facilities.
Jim Davison, South of England Region Director at Make UK, represents manufacturers in the UK and says, “what is clear is that predictive maintenance can play a crucial role in reducing costs and boosting productivity. Especially when manufacturers need to use every tool at their disposal to meet the demands of an ever-changing industry."
Senseye’s study also showed that more than two-thirds (72%) of large industrial organizations had made predictive maintenance a strategic objective. One in five (20%) have established in-house predictive maintenance teams to lead these initiatives.
51% of organizations said they already performed condition monitoring, and 87% collected at least some data used to support predictive maintenance.
Senseye’s research comes from interviews with engineering and IT professionals at 72 multinational industrial and manufacturing companies in 21 countries. We estimated the level and cost of unplanned downtime experienced by FG500 companies by extrapolating our research findings with publicly available information on the number of plants operated by these companies and the people they employ
Victor Voulgaropoulos, an Industry Analyst at Verdantix, the independent tech research and advisory firm, says that “Senseye’s investigation into the costs of unplanned downtime highlights just how much-untapped opportunity there is right now for industrial organizations to save money through widespread adoption of software applications and technology-enabled maintenance practices.”There are more statistics and insights in our The True Cost of Downtime report, which you can download here.