However, the vast amounts of data generated by smart manufacturing need to be harnessed, stored, and governed. Siloed data infrastructure is a common pitfall in digital transformations. According to Gartner, Inc., 82% of CEOs in supply chain-intensive industries plan to increase investments in digital capabilities, but only 32% of digital supply chain roadmaps are aligned under a single governance process with common business goals. Master data management and creating a single version of truth across all data related to a manufacturing business can provide a context for the IoT to function, fueling the efficient and accurate use of AI, digital twins, and other smart manufacturing initiatives.
Key takeaways:
- The Fourth Industrial Revolution, or Industry 4.0, is all about data and innovative technologies that improve business efficiencies, with Industry 5.0 already being used to describe the collaboration of AI and robotics with humans.
- Smart manufacturing is no longer a choice for manufacturing companies, but a necessity for survival and growth. It involves implementing technology to make businesses more efficient and save costs, with benefits such as reducing machine downtime and costs of inventory utilization, increasing throughput/output, improving forecast abilities and increasing the efficiency of human labor.
- Key elements of smart manufacturing include the Internet of Things (IoT), AI and machine learning technologies, predictive maintenance, robotic process automation, edge computing and the digital twin—a simulation allowing engineers to work through crucial what-if situations.
- Master data management and creating a single version of truth across all of the data related to your manufacturing business can provide a context for the IoT to function. It creates a platform that fuels the efficient and accurate use of AI, digital twins and all of the other smart manufacturing initiatives.