Earlier this year, I had the opportunity to tour a large semiconductor manufacturing plant. The company didn’t have a manufacturing execution system (MES), so the people relied on a variety of applications and spreadsheets to run the plant. One process called for operators to transcribe machine data to paper, plus manually enter the same data into another machine five feet away. Manual machine-paper-machine processes just like this are one of the biggest roadblocks to achieving industrial transformation (also smart manufacturing or Industry 4.0), and they’re more common than you might imagine.
LNS Research data shows that 80% of manufacturers don’t have an MES application and use spreadsheets or paper-based processes to run plants. Yes, these companies are significantly behind in today’s industrial revolution. However, they need not worry that they first have to implement MES before starting the industrial transformation journey.
The industrial transformation road isn’t the same for every manufacturing company. More mature organizations ― the early adopters that already have automation enabled and MES in place will have an easier industrial transformation journey. For everyone else ― what's ahead isn’t quite as easy, but if they follow a proven industrial transformation framework, they can skip a few steps and jump from paper-based processes directly to MOM applications on IIoT platforms. These are the steps required to get started, catch up, and make the road easier along the way.
Industrial transformation initiatives deliver the greatest impact when designed top-down and executed bottom-up. The future state for the plant must align with the company’s overall strategic objectives. However, it’s possible for a plant to act on its own. For instance, the shop floor can start collecting data, make it available to share throughout the plant, and deploy a plant-wide MES solution. This approach enables immediate operational improvements at the plant level, but as the plant manager you should make sure the short-term benefits don’t overshadow and deviate from the company’s strategic objectives.
When the shop floor aligns properly with corporate strategic objectives, it’s in a position to produce long-term benefits, but that doesn't have to mean connecting and automating every single asset. Most successful industrial transformation projects get started with one or two small projects involving just a few key machines. Focus on getting the right information to the right people, and scaling things up as required.
For several decades, any organization searching for manufacturing software to run the plant had few options. Not many MES/MOM solutions did a finite set of tasks with minimal integration to even an ERP system. Those days are over. Today, large ERP vendors, automation companies, product design and control systems companies, IIoT platform providers, and start-up software companies sell across the MOM space. Every software company has its own flavor of manufacturing software ― ranging from standalone MOM to MOM apps on an IIoT platform.
While some of these solutions score high on integration with other enterprise solutions, they might not be not so good with data management or analytics. Today’s manufacturer can choose MOM that aligns with their vision ― and it doesn’t have to be from a pure play MOM vendor. This is one more reason to align with corporate strategic objectives. Operations executives that seek out and understand the big picture are more likely to choose the right platform and enable true industrial transformation.
The usual suspects in most smart manufacturing initiatives span 3D printing, smart connected assets, the extended supply chain, remote operations centers, and many others. The common denominator across these initiatives is data. As manufacturers consider use cases, they’re also thinking about how to automate data collection, build an operational architecture to make the data available across the enterprise, develop new business cases around the data, run advanced analytics on the data to identify patters, and build dashboards and mash-up apps.
A common theme in the analytics arena is “big data.” While most factories claim to have big data and run analytics on it, most of the time they’re only providing the same old answers to the same old questions ― like, “How do we reduce the downtime of asset A by 5% to increase the OEE by 3%?” While that’s good information, it’s not what industrial transformation is about. True industrial transformation with big data analytics serves up new answers to new questions; the plant manager should get answers to questions they didn’t know to ask in the first place.
The fourth industrial revolution has taken off considerably well in the last few years, and things like Industry 4.0, smart manufacturing, or industrial transformation are on the mind of every manufacturing executive. Industrial companies at varying stages of maturity have found ways to get started despite their software status.
It’s possible that a company with mature software adoption and capabilities can be half-way through its industrial transformation journey. The less mature organization doesn’t necessarily need to follow the same path; it can skip ahead by taking the right steps:
Learn how industrial companies put Industry 4.0 to work in the research eBook, “Smart Manufacturing: Smart Companies Have Made Smart Manufacturing the Center of the Enterprise.”