Though manufacturing is rebounding, a 2019 dip reminds us about the importance of maximizing productivity and efficiency and decreasing downtime and operational expenses for optimal growth and profit. Smart manufacturing helps in all these areas while filling in a widening skills gap. Beyond the production of goods, digital technology can be applied to product innovation, planning, and supply chain logistics, in the field and on the floor.
Creating a Smart Manufacturing Enterprise
Many companies have already invested a great deal in manufacturing automation over many years. Intelligent solutions build on these efforts and take the processes to a new level. Digital technology isn't about rip and replace; the promise of smart machines—intelligent processes and the industrial IoT lie in connecting all the systems. When automation is linked to ERP, scheduling and product lifecycle systems, the result is a smart manufacturing enterprise.
At the outset, analytics gleaned from instrumenting equipment with cost-effective wireless sensors and connecting to the cloud will improve asset performance. These digital tools will allow easy data capture in the factory and from the field and seamless processing for conversion into real-time actionable information. This is the start of better business decisions and forward-looking processes.
People working collaboratively with the technology will rely on devices, data analytics, and transparent connectivity to increase productivity and overcome a shortage created by the shifting labor market. A rise in baby boomer retirement is giving way to a new generation of employees— those who were raised in the digital age and expect technology will help them do their jobs. This means that while smart manufacturing is machine-centric, it must also be more user-centric.
In this new, smart environment, we’ll find greater enterprise control. Machines and manufacturing assets will be integrated with the wider enterprise. Unifying systems will usher in more flexible, efficient and, ultimately, more profitable manufacturing.
How to Start Maximizing Operations
This type of operation first requires a robust data infrastructure to build high-performance machine learning and bring all the pieces together. Creating data infrastructure starts with the instrumenting, ensuring telemetry and connecting disparate systems. A consistent model across systems will deliver higher-value analytics to enable enterprise-level control and the context to gain meaningful insights.
Prior to making such technology investments, companies should determine the business drivers. Let’s say an organization wants to up capacity in its existing footprint to meet more demand. Increasing operational productivity and volume while using current assets available could involve a tactical operational deliverable around product mix and uptime. Are specific assets in the process slowing down the overall effectiveness? What software or technology can be integrated into those products and the current technology footprint for higher availability?
Schneider Electric’s EcoStruxure Augmented Operator Advisor is a smart tool that helps answer those questions. It allows companies like Becton Dickenson to increase efficiency and decrease costs through virtual maintenance and instant diagnosis related to system problems.
From a manufacturing perspective, some industries are further along in their digital transformation journeys than others, so the conversation should be based on the maturity of the segment and business requirements. Small wins are ideal to start. ROI in the short term is as important as the long-term transformation. Manufacturers should take it one step at a time.
If an existing operation is mature enough, the focus should be on agility through even more digital transformation. Thriving in the future will depend on, at least, maintaining and, even better, increasing digital infrastructure investment. The more sophisticated the deployments, the more easily a manufacturer can react and adapt to the complex 2020 landscape.
Overall, any manufacturing facility should be agile enough to change volume and mix in a cost-effective manner. Some of this flexibility is addressed in physical infrastructure but a great deal more is in the data infrastructure.
In times of economic uncertainty caused by the disruptive effects of tariffs and trade wars, global health crises and a widening skills gap, manufacturers need digital technology to stay competitive and navigate the complexities.
