Smart manufacturing shouldn’t be a leap in the dark. In the first of this series of posts, we highlighted the risks of investing in any new system before the return on investment (ROI) had been identified. The good news is that, across the manufacturing sector, there are considerable opportunities to realize significant and quantifiable financial returns. With the right support, it is perfectly feasible to calculate them ahead of decisions regarding deployment.
Areas enterprises could explore to identify ROI include the potential to reduce lead times and boost throughput by optimizing production parameters and using root cause analysis to address bottlenecks. Predictive maintenance can cut downtime and extend the working life of machines. Product quality can be enhanced, and warranty costs reduced, using techniques such as post-sales analysis.
Whatever the precise objectives for smart manufacturing, putting together a robust financial proposal on which sound investment choices can be made is the strategic starting point for the journey. Moreover, it should represent the first step of a carefully structured workflow.
Once value has been established, the next stage in that workflow involves harnessing the data. In many applications, existing production equipment will already be generating plenty of useful information. If not, a manufacturing plant can be retrofitted with the necessary sensors.
But this is far from the full story. Converting that raw data into a useable, clean dataset is also essential. With data more than likely coming from varied sources and in different formats, data transformation is critical to accomplish consistency – a requirement for machine learning (ML) algorithms to be utilized effectively.
Building and testing those ML models is the next step. As we’ve also stressed previously, algorithms should be shaped by domain expertise. This does more than ensure that meaningful and accurate insight is generated. It also engenders a real sense of ownership among the people whose decisions will be guided by the new system. Smart manufacturing needs to be perceived as a solution that has been developed within the manufacturing domain, not imposed by the world of IT.
That’s why capability and accessibility go hand in hand. With algorithms deployed, the use of intuitive, no-code systems will engage and enable manufacturing teams. Even relatively simple functionality, such as the ability to customize dashboards, will help forge the relationship between a new system and the people directly responsible for securing the intended benefits. That in turn will help facilitate the final step in the workflow: real-time monitoring of the anomalies, outliers, trends, and relationships that fuel a process of continual improvement.
No one understands the importance of a seamless and logical workflow better than the manufacturing sector. From initial concept through to achieving the desired ROI, that’s exactly what the deployment of smart manufacturing demands. At Altair, our portfolio encompasses all the elements needed for a fully integrated solution that delivers in practice what it promises on paper. To find out more contact us or download a complimentary copy of our new smart manufacturing e-book.
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