The customer is ready to order but needs to know the price and delivery date first. You check finished parts inventory, material availability and machine capacity. There are phone calls, then judgment calls. Voices are raised, risks taken. The customer gets his quote eventually, but maybe too late.
It’s a hypothetical scenario yet one that plays out in manufacturing operations every day. The challenge is the data: if it’s available. The data is often buried in siloed systems, just plain not accurate and or stored without enough detail or context. Management is left using estimates and gut feeling rather than analytical decision-making, which is no way to run a business.
Shop floor digitization offers a better way. The data you want is there but it’s buried deep. It requires sensors, connectivity and cloud computing to draw it out in context.
Products are digital: they live as computer-aided design (CAD) models and simulations. Enterprise resource planning (ERP) has digitized business management and manufacturing has been digital for decades: programmable logic controllers (PLCs) and PC drive motion, robots and even inspection, all without human input. What’s missing is the connectivity.
Shop floor digitization is about linking all those systems and turning data into information. Specifics will vary by manufacturer and manufacturing process but there is a common theme: connectivity. Query connected machines and you will have real-time data on their condition and availability. Link this live process-level data with production order data and you’ll also know the status of every job on the floor along with material yields and inventory levels.
Now send this data to the cloud and let employees access it as and when needed. Suddenly data becomes information that drives better decision-making. Workers are empowered to investigate and experiment. Waste and costs fall as capacity and output grow.
Some might see this as an impractical dream. However, here are three use cases to consider:
Empowering Continuous Improvement
No one knows the processes and machines as well as the people who work on them. They see and live with the problems, but without data, they are often powerless to make changes. Too often the correlation between item-based production data and equipment performance are lost in the data tsunami. It feels like certain parts are more problematic to make and now the data assists in determining just how problematic and provides the basis for addressing the issues. When production statistics go to the cloud, they are accessible to all. Given tablets or PCs to view the numbers, workers can review and Pareto problems, prioritizing and acting without waiting for engineers to study or managers to make a decision.
Increasing Asset Utilization
Planned maintenance aims to prevent major breakdowns, but many machines and lines are plagued by micro-stoppages that get little attention. Automated reporting directly from the equipment yields data on actual performance, minute-by-minute if needed, giving a level of granularity never before available. And once problems are known, they can be fixed.
Machine conditioning monitoring takes this further. Cloud-based AI can monitor key machine signatures and decide when maintenance will prevent quality problems or downtime. Then the computerized maintenance management system can check spare inventory and even schedule repairs in a way that minimizes production impact.
Manufacturers, especially those in the automotive sector, have been getting leaner since at least the 1990s, but you will still see inventory on the plant floor. Perhaps an order is waiting while a machine breakdown is fixed, or maybe a tool is being repaired. Accurate, up-to-date data such as machine condition, tool condition and parts availability could eliminate this challenge. This leads to less works-in-progress and shorter lead times, freeing-up space otherwise occupied by delayed production orders while improved cash flow delights the company’s Finance department.
Rather than diving straight in, consider a pilot study. Instrument a machine or part of the process, gather data, align it in context and determine what it’s telling you. Over time you’ll be able to correlate changes in these signals with events and identify what is and isn’t useful. In parallel, investigate cloud storage and learn what data analytics can do for you.
QAD has already engaged some of its customers via QAD Labs, the company’s virtual collaboration hub for advanced technology experimentation, to target and address the challenges associated with manufacturing planning and business operations. If you are interested in learning more about QAD Labs, have a need or idea, please let us know at QAD_labs@qad.com.
Make the Move
Manufacturers around the world are recognizing that information is key to improving their competitive position. Information comes from the wide variety of data associated with the operational and planning systems supporting a factory. Shop floor digitization is the basis for meeting the challenge of converting data into better decision making and corrective action. Instrument your machines, gather data, build context, share it via the cloud and let it guide your employees’ decision-making. You’ll see your business become leaner and more responsive with costs falling and capacity growing.