Vatsal Shah leads the management and engineering team as Co-Founder and CEO at Litmus.
Talk of smart manufacturing has reached a fever pitch in the past year, but recent market conditions shed light on where most manufacturers stand in their journeys to digitize the factory floor. Many manufacturers were caught “with their pants down” so to speak, perhaps with multimillion-dollar Industry 4.0 or IoT initiatives in the works, but without any results to show for their efforts.
Working in industrial engineering, electronics system design and IT ecosystems over the past 10 years, I’ve seen the slow progression toward Industry 4.0. As the Founder and CEO of Litmus, I help companies rapidly embrace smart manufacturing to make better business decisions, which has never been more critical than it is today.
As a pandemic swept the globe, there were quickly winners and losers as an incredibly important driver emerged on top of the age-old manufacturing focus on quality and operations — agility. Winners were agile, they were responsive, they adapted.
Ford Motor Company lent its manufacturing expertise to the medical industry to build lifesaving machines and equipment. Bacardi manufactured hand sanitizer, and Purell dramatically increased production. Nike added face shields to its product line and Gucci made face masks.
On the other hand, many toilet paper companies, such as Angel Soft, couldn’t keep up with demand because their factories were already at 100% production during normal times. The meat processing industry has been slow to embrace robotics, which likely added to its inability to adapt to coronavirus outbreaks and restrictions.
The moral of the story is this: Those large, bulky, difficult-to-implement IoT initiatives should be put on hold in favor of simple smart manufacturing solutions that can make a manufacturer more agile immediately.
How Smart Manufacturing Increases Agility
Manufacturing agility, worker safety and continuity of service are critical, and smart manufacturing can help companies be prepared to lead the way in all of these areas.
1. Find and solve bottlenecks quickly: Collecting operational equipment data like cycle time, downtime and uptime allows manufacturers to paint a picture of what is happening on the shop floor so they can identify process bottlenecks and fix them.
2. Improve operational performance: The value of smart manufacturing is realized with real-time actionable insights via data analytics such as waste reduction, asset utilization, downtime, anomaly detection and more. These analytics can be used to drive business decisions to achieve targets and predictability.
3. Break down organizational silos: Some manufacturers are collecting data, but the data is siloed and only available to either operational or IT teams — not both. A smart manufacturing platform can provide a complete data picture with visibility for both expectations and real-time performance that should be shared across the entire corporation.
4. Support predictive maintenance: Data can be used to deploy machine learning models that lead to higher quality products and predictive maintenance. Machine learning capabilities can be used to predict and prevent disturbances before they impact operations.
5. Increase workforce productivity: Smart factory data can be accessed at home, via smart phone, in the corporate office or on the factory floor. With or without a global pandemic, the ability to manage devices and access data remotely empowers employees and helps manufacturers make better business decisions.
McKinsey reports that implementing an agile transformation can improve operational performance metrics by 30-50%. A smart manufacturing plant is an agile manufacturing plant.
Digital Transformation To Meet Changing Market Demand
So why have so many companies started digital transformation initiatives but still don’t have a fully connected shop floor sending useful data across the enterprise? In my experience, many manufacturers have lumped smart manufacturing in with larger IoT initiatives. They are hesitant to invest in new technology in the current economic climate. The fact is, however, that manufacturers can’t afford not to invest in digital transformation to meet rapidly changing market demand.
Data is already available in droves; computers are all over the manufacturing enterprise and sensors are pervasive on the shop floor and across the supply chain. However, many companies have not put the technology in place to use that data effectively. They are leaving intelligence sitting in data warehouses with nowhere to go.
Manufacturers simply need to start by thinking about where they need to go to become more agile. This list likely includes the need for connected assets, all the technology in one platform to easily collect that data, process and analyze it, and the ability to share the data with stakeholders.
Smart manufacturing doesn’t require an entire team dedicated to its success. Start by getting both IT and OT stakeholders on board. They need to sit at a table together and agree upon the end goal for the smart manufacturing initiative. Then, factories with connected assets can add a layer of intelligence on top to access that data and share it across the enterprise.
What appears to be overwhelming for the operations or IT teams looking for these solutions is that everyone calls them something different: an IoT platform, an Industry 4.0 platform, a smart manufacturing solution. Remember, the name of the technology doesn’t matter; what it does and how quickly it can do it matters. There are solutions out there that can be implemented in less than 30 days. Companies can continue to support their long-term IoT or Industry 4.0 initiatives, but they can collect and make use of the data they have now with a small investment of time and money. There are all-in-one platforms for smart manufacturing that reduce cost, complexity and risk.
Not surprisingly, the aforementioned Ford Motor Company has already invested in connectivity, mobility and data analytics. Bacardi also has a strategy for data analytics and actionable insights. Purell is monitoring hand sanitizer dispensers with IoT and Nike uses predictive analytics.
Right now the need for smart manufacturing is even more critical to improve the way manufacturing companies do business; to perfect the process, to conquer bottlenecks, to improve quality and to ramp up production when needed to meet market demand.