The primary applications of data and analytics impacting the manufacturing ecosystem involve smart product design and quality control, smart production planning and process optimization, equipment maintenance, and others.
FREMONT, CA: According to a study, over 85% of industrial manufacturers believe that smart factory projects will be the primary driver of manufacturing competitiveness in the next five years. Industrial Internet of Things (IIoT) is vital to the smart factory ecology. Flexible systems self-optimize performance across a network of suppliers, factories, and partners; self-adapt to and learn from new conditions in near-real time; and autonomously run entire production processes.
Operational data is the elemental force behind the seemingly magical future in manufacturing. Manufacturers are ever more collecting data from automated sensors in real-time, storing it in the cloud, processing it through algorithms, and visualizing it for a range of applications. As Information Technology (IT) and Operational Technology (OT) converge in the smart factory–in equipment, information systems, products, and users—the variety, volume, and complexity of data are exploding.
So, how are manufacturing heads unlocking value from the IT/OT data growth? It is hard to keep up with all of the new potential coming online. At one stage, typical phases of value creation entail a data lifecycle, usually inclusive of data generation, collection, storage and integration, transmission, processing and analysis, application, and visualization. As in other businesses, analytics then run the scope from descriptive and diagnostic to prescriptive and predictive. Nevertheless, it is the expanding use cases for the diverse data and analytics that command the focus at center stage for business impact in manufacturing. Foremost among the applications are:
• Smart production planning and process optimization.
• Smart product design and quality control.
• Manufacturing process monitoring and adjusting.
• Material distribution and tracking (logistics, traceability, and others).
• Equipment maintenance.
Experienced plant managers are connecting the data lifecycle into industrial units and applying advanced analytics to enable these and other capabilities. The outcome is business processes and decisions that amplify output, productivity levels, utilization, and therefore result in higher revenue, reduced risk, and lower cost.
However, a few companies have made the journey into smart manufacturing at scale by authorizing analytics in their factory network. Advances on the maturity curve are burdened with potential stalls and complexity. Before driving innovation, proving ROI, and staying ahead of emerging trends, manufacturing leaders ought to overcome decisive workforce challenges, dangers in data management, and cyber threats.