What’s In Store For Industrial DataOps In 2023?
As manufacturers set their eyes for a new year, it is important to have a clear idea of what their priorities must be to grow and succeed. The first thought that may come to your mind in this direction may be the trend of smart manufacturing wherein emerging technologies like cloud, IoT, analytics, AI, etc. reshape traditional manufacturing approaches to help manufacturers embrace autonomous operations with higher productivity, increased competitiveness, and lower cost. But to go deeper in this direction, manufacturers need to get their fundamentals right and ensure that their operating models can accommodate this transition to a smarter ecosystem. With the growth in the adoption of MES, manufacturers were able to bring in a higher level of digital transformation within their operations. But to progress further, the need of the hour is undoubtedly “Industrial DataOps.”
What is Industrial DataOps?
In simple terms, Industrial DataOps refers to the initiatives that work on data generated by manufacturing systems to turn them into insights that can drive decision-making across multiple areas. MES creates an ecosystem where different digital systems within a manufacturing business supply operational data. Industrial DataOps solutions leverage this data to uncover hidden potential for growth, productivity improvement, cost reduction, and other strategic advantages for manufacturers.
What does 2023 hold for Industrial DataOps?
For manufacturers who capitalize on leveraging Industrial DataOps solutions, 2023 promises to be a very fruitful year. Let us explore some of the top possibilities that Industrial DataOps can help realize in the new year:
Extending the life of assets
One of the biggest concerns that manufacturers face every year is the escalating cost of maintaining their facility infrastructure in optimal condition. This includes keeping all machinery properly serviced and maintained for maximum utilization with minimal wear and tear. Industrial DataOps can help bring a new lease of life for machine health within manufacturing facilities. By acquiring data from connected sensors on machinery, Industrial DataOps allows manufacturers to understand working dynamics and predict when a machinery or its component will need periodic maintenance or replacement. It can decipher hidden traits of wear and tear from performance data and correlate the same with maintenance cycle data to accurately estimate the next schedule of maintenance activities. Advanced knowledge of maintenance cycles helps manufacturers plan more cost-effective maintenance programs through negotiations with multiple vendors.
Improving visibility
Large manufacturing facilities may have a lot of automation. But business process automation is only successful in collaboration with employees. For example, large manufacturing facilities have several human personnel managing operations in several critical areas, including real-time maintenance. Industrial DataOps brings visibility into diagnostic and operational data by all relevant stakeholders. This is especially useful for field maintenance staff who periodically check machine health. Industrial DataOps help design maintenance programs that automatically guide field engineers to the exact component within machinery that needs attention. This inference arrives through careful analytical processing of the historic performance data of the machine, which can reveal the most ideal scenario for a specific behavior anomaly.
Modeling new use cases with data
Manufacturing is an industry that has traditionally relied on physical processes to generate revenue, making it difficult to directly monetize data generated from digital systems. However, with the emergence of Industrial DataOps, manufacturers can leverage the power of data to optimize production processes and drive innovation. For example, Industrial DataOps helps enterprises capture the right data from equipments, allowing data scientists and analysts to use this data to model operational scenarios wherein machine utilization is optimal, inventory planning is aligned with market demand, and machine health is at its best performing level. Rather than having to build the entire hardware from scratch, Industrial DataOps allows manufacturers to build a digital twin with accurate data behavior as a real-life machine would exhibit. This allows them to forecast failures, determine the best operational routines, and much more.
Lowering costs
As the competition tightens, manufacturers must remain focused on delivering high-quality products faster to the market. However, this should not incur a major cost escalation. With Industrial DataOps, we have seen how machine health improves, employees manage operations optimally and capital expenditure is reduced via modeling through digital twins. Ultimately, all these efforts will contribute to lowering overall operational costs for manufacturing products.
Industrial DataOps offers manufacturers a bright future, unlocking numerous opportunities for sustainable growth and profitability. To fully embrace digital transformation in manufacturing, companies must recognize the value of Industrial DataOps and choose the right tools and platforms. Rawcubes' Industrial DataOps platform is tailored to meet the unique needs of the manufacturing sector and drive successful outcomes. Contact us to learn more about how we can help you achieve your goals.