Making manufacturing maintenance pay

In an industry facing mounting pressure from squeezed margins, ageing assets and a reduced workforce, manufacturers are understandably targeting maintenance as an area to unlock greater productivity and profitability. While existing reactive and preventative solutions offer a degree of support in easing maintenance costs, significantly enhancing the performance of maintenance strategies requires a more pro-active approach supported by intelligent software.

At present these solutions are limited which highlights that there is a gap for technology providers to fill if manufacturers are to have the trust and confidence to break away from traditional maintenance methods.

In sectors that share notable synergies with manufacturing, including oil and gas, wind, power generation and aerospace, maintenance managers are experiencing significant profitability and productivity improvements due to new predictive maintenance solutions. These highly intuitive solutions use asset condition data to predict failures and thereby only schedule maintenance when necessary. The resultant benefits are clear. In a new report by Castrol’s innovation arm, Castrol innoVentures, and Roland Berger Strategy Consultants, a leading global consultancy, energy companies eliminated on average 75% of breakdowns through the use of predictive maintenance techniques. Furthermore the average cost for power plants operating a predictive maintenance programme on their pumps was found to be 9 USD/hp per annum, compared to 18 USD/hp per annum for reactive maintenance and 13 USD/ hp per annum for preventative cost.

Overcoming barriers

However according to the report Predictive maintenance: Is the timing right for predictive maintenance in the manufacturing sector?, manufacturers are yet to reap these widespread benefits. This is in spite of some best-in-class organisations already introducing predictive maintenance and experiencing notable successes. For example, some manufacturers have reduced unscheduled downtime to about 5% below the industry average and achieved an increase in overall equipment effectiveness (OEE) of more than 8%. Furthermore, the report identified that manufacturers have an appetite to increase the time spent on developing predictive maintenance solutions from 15% to 33%, while reducing spend on reactive and preventative maintenance.

With these benefits and notable market interest reinforcing the relevance of exploring new predictive maintenance technologies in manufacturing, why are similar technologies yet to be widespread? The answer is multifaceted and driven by a number of practical barriers that are unique to the complexity of the manufacturing sector. These include the wide and complex range of critical equipment that is used as well as diverse and dynamic operating conditions, which can be technically challenging for solutions providers. Similarly, budgetary pressures and a cultural inertia towards reactive maintenance still need to be largely resolved in order achieve widespread adoption of predictive maintenance in manufacturing.

Amid these challenges, and although there is a growing awareness of the latent potential in predictive maintenance strategies, this is yet to translate into widespread behaviour as engineers are still commonly defaulting to traditional maintenance methods. However, with significant added value on the table – from reductions in unplanned downtime, to asset lifecycle extensions, elimination of unnecessary maintenance tasks and component replacement cost reduction – Castrol maintains that by transferring knowledge gained by the early adopters of predictive maintenance solutions and the right technology systems to support this, it will be only a matter of time before manufacturers too can drive efficiency and significantly lower costs on a more widespread level. 

Problem solving

Like any development opportunity, predictive maintenance requires ongoing investment if it is to be a success in the manufacturing industry. This is a challenge when there are many operational priorities that are competing for resources. To overcome this, Castrol is calling on entrepreneurial predictive maintenance providers to adapt their solutions to the manufacturing space and for those who do have an offering, to come forward and collaborate to increase trials and uptake. Based on the considerable efficiency savings achieved in analogous industries, developing predictive maintenance in manufacturing companies could deliver a win-win; opening up a new market for solution providers and driving increased profitability and productively that will enable manufacturers to remain competitive amid tough market conditions.

With maintenance increasingly seen as a strategic business function by manufacturers that are looking for new opportunities to drive efficiency and lower costs, can technology providers afford not to initiative dialogue about new solutions that meet the varied and complex dynamics of manufacturing when so many benefits are at stake?