Big data is nearly everywhere now and can be used to improve your manufacturing. You can already see its impact in your everyday life. It’s in the supermarket you visit with the codes and tracking on every package. It is in the data evaluated on every internet search you run. Data is also growing and will be a changing factor in sectors like health care systems in the coming years. McKinsey estimates that big data could generate up to $100 billion in value annually in the United States’ health care markets alone (https://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/how-big-data-can-revolutionize-pharmaceutical-r-and-d). The growing wave of big data is already huge in business and industry, but there is a lot more coming. The International Data Corporation estimates that “big data and business analytics will grow from $130.1 billion in 2016 to more than $203 billion in 2020” (https://www.idc.com/getdoc.jsp?containerId=prUS41826116). When even the United Nations believes that big data can have a ‘big impact’ towards improving the world – then there is no way to deny that the incredible value of big data has been realized (https://news.un.org/en/story/2017/05/557492-big-data-can-have-big-impact-achievement-global-goals-un-says-it-day). Big Data is everywhere – and it is available to help your manufacturing operations, but are your manufacturing operations ready to use big data?
Big data is impacting business decisions every day – and its growth in manufacturing industries will be at least as big as it is in the rest of the economy if not bigger. Some manufacturing big data capabilities like coding and traceability data is already almost ubiquitous. Areas of pharmaceutical manufacturing cannot even operate without full lot-tracing on all products. Quality assurance and vision inspection systems are increasingly used to monitor and verify quality on every package, corrugated box, folding carton and bag that passes through a manufacturing line. These systems can scan to ensure everything from accurate packaging colors are applied or to confirm all required labels are placed on every package. Quality assurance procedures can verify that proper hot melt applications are set on every carton or case created online, running at high-speed. Inspection technologies like the use of X-rays are used on products to make sure there are no metal fragments to be found in shampoo bottles or yogurt containers. Quality inspection systems also generate some of the best big data to help you maximize your manufacturing operations.
As any plant with an inspection and data collection system can attest, big data can quickly play a pivotal part in advancing your manufacturing facility. However, the scale of the data collection can get confusing in a hurry. On large manufacturing lines that are increasingly automated and sometimes running with a single human operator, there can be massive amounts of data being collected continuously. For instance, by the time a product is finished and palletized, a plant could have collected data-points including:
- Electronic images for all sides of a product and its package to guarantee image quality and colors
- Complete measured dimensions of a box to validate perfectly square packaging
- X-rays of product contents to make sure no debris or contaminants are included
- Data on tracking codes and verification that all packaging stickers have been placed correctly
- Verified hot-melt seals for every single box, carton, package or bag manufactured
Those are just some of the data-points that can be collected through different quality assurance processes. In a corrugated box making plant that produces about 20,000 boxes an hour while operating 20-hours a day for approximately 340-days per year – it is straightforward to see how data can become very very BIG in a single day. That data can be useful when reviewing both a fault with an individual package in real-time on the factory line or later with a customer weeks or months after it was delivered. It can also help track the date of manufacture and shipping for an individual folding carton. All those data-points also build into incredible elements that will help you evaluate and improve your operations. Big data can help identify both small issues like the under-performance of a specific piece of equipment or can help you identify whole new areas for improvements on your manufacturing line.
Best Manufacturing Uses for Big Data
Big data does bring some exciting possibilities for industrial manufacturing. But, for manufacturers like you, there are some critical things to strategize about before you get swept up in the movement. Specifically, there are a couple of considerations that you need a plan for before you implement new collection systems:
- What are you going to do with all of your big data? How will you use the information to help your operations?
- Where are you going to store your data and how long will you keep it?
Both of the above are significant points to consider, but the first one is the most critical decision you will make regarding any information your manufacturing plant may collect. Just as data is only big when there is a lot of it, so too, it is only important if you have a plan on how to use it in your operations.
In manufacturing, big data can help in numerous ways, but some of the most obvious uses for data include:
- Using data trends as indicators to make machinery adjustments such as altering performance settings. This information can help correct errors or identify service needs through early-detection of signs that consumable parts will need replacement soon.
- Review your manufacturing performance data related to the line operators working during sessions. Is there an equipment setting or procedure that a line operator is missing that causes problems? Could a short training-refresher solve some of your operating issues?
The two big data uses above are good examples of the difference between just having big data and actually using big data to drive your manufacturing improvements. Achieving things like increasing the overall equipment effectiveness (OEE) and having line operators who implement the optimal systems and standards on every shift could completely change your operations. Data can reveal your best opportunities to improve your machinery and/or performance of your line operators. Big data can notify you when consumable parts are nearing the need for replacement before they break and cause damage. Big data can even highlight problematic equipment where a replacement might offer an immediate ROI and quick payback. You can use big data to reduce or eliminate faulty packaging and defective products produced on your line. Reducing downtime with data support is already here, and all that data could one day reach into obscure areas of your operations such as identifying the environmental conditions that your plant operates most efficiently at.
If you don’t already have it, big data will be coming to your manufacturing plant. That is inevitable. It will be more prevalent every year. Most new manufacturing and industrial equipment have data collection and reporting capabilities. Which pieces of big data you can benefit most from analyzing is the key to your manufacturing improvements that you should start evaluating today. A PwC industry report last year stated,
“Industrial manufacturers will have to figure out how to manage the data coming from an avalanche of sensors, integrated equipment and platforms, and faster information processing systems. … (T)he anticipated efficiency returns from digitization over the next five years across all major industrial sectors are substantial: nearly 3 percent in additional revenue and 3.6 percent in reduced costs per year. “(https://www.strategyand.pwc.com/trend/2017-industrial-manufacturing-trends)
This change is to take place in just the next five years. For manufacturing companies that resist jumping onboard with big data advances, dangerous days are coming. The revenue increases and cost reductions reported by PwC may be the differences in manufacturing efficiency that determines which manufacturers survive and which fail in the global economy during the next five years.
Big Data is Important Today
However, big data is not just about the distant future or the next 5-years of manufacturing operations; It is about right now. Today, with decisions you make regularly, big data can help you make them better. For instance, you probably have regular (daily, weekly, monthly) reviews of your spot check results. You may even be looking to evaluate where you are in the journey to achieve the elusive Six Sigma defect rates. However, with traditional spot checks only looking at a tiny number of total packages, boxes, cartons, packages, or bags, you will always have to worry about the misfortune of pulling the wrong box and missing defects. Furthermore, pulling the wrong package will send you looking for issues that do not actually exist, rather than addressing the true nature of what is occurring. Without big data, no one can immediately identify whether an issue is a trend affecting many of your products or just a random occurrence impacting a small number of products.
When a spot check pulls a package with faulty adhesive applications, how long is spent checking other packages and investigating what problem created the fault? What if misfortune had an operator pull the one defective box out of tens-of-thousands of packages with perfect adhesive applications? Think of the time lost. Big data derived from an automated quality assurance or visual inspection system that automatically ejects a faulty package, would also be a night and day difference in identifying whether you have a random package fault or an actual defect trend. This action can be taken immediately at any point during a shift or even on regular monthly reviews. Big data collection can show results from every single package that runs through your line during this shift as well as dating back months or years. So, not only will you know your exact production defect rate, you will be able to remove such defects automatically before shipping, and you will have the ability to differentiate between a single error or trending defects. These are the types of improvements that make big data sound pretty great, right?
Where Should I Start with Big Data?
Jumping into big data already has a ton of options that can offer immediate impacts on your manufacturing operations. A great starting point might be a vision inspection or quality assurance installed to scan every individual package, box, carton, or bag assuring that every product leaving your manufacturing line is in excellent condition. Such quality assurance and inspection systems can help you take big data from a concept to an easily-implemented action that makes your manufacturing better. There are so many significant data opportunities to select from with inspection systems, and each of them will help keep your plant competitive. Examples of where data collection on your lines can benefit include:
- Data collection that helps identify the source of problems or faults on your line. For instance, big data’s individual images of glue faults will help diagnose if the defective products are the result of an empty glue container, a problem with the pump or a dispenser/applicator head problem. However, longer-term defect data trends can indicate shift crew or machine problems that may be recurring or worsening due to maintenance issues. Harvesting this valuable big data for worsening or improving trends forms the foundation for the process, maintenance improvement, or accolades for personnel that work on the lines.
- Vision inspection systems that identify printing errors on your line. An inspection system can eject any package with a faulty barcode or poor image quality, but it can do more by recording every variable code for inclusion in data shipped to your customers with all the boxes. If problems are found, your mixed media data inspection system can be used to rapidly identify if the cause of the issues is a damaged print plate, an ink shortage or even if a line operator accidentally added the wrong color ink during the last refill. All these benefits also apply to flexo-printing products as well, where solid inspection systems will grade code quality to prevent poor flexo printed codes from being shipped.
- Many inspections systems can integrate with your current manufacturing equipment. For example, with folding carton manufacturing, there are vital folds completed that are not visible to the naked-eye during high-speed operations. Inspection systems are available to verify correct folds, identify faults and help address issues immediately as they develop. These systems can be integrated with your current folding machines and can show fast ROI.
- Help your manufacturing line operators perform better. Mistakes happen in every office and plant, but there is not always a way to find out who made a mistake and help them learn from it. In a folding carton plant, an employee might repeatedly set up machinery incorrectly by switching folding rails to an outside tab when it should be an inside tab. Or, in a corrugated manufacturing operation, what if an operator feeds corrugated boxes backward into machinery and causes asymmetric scores that lead to misaligned flap wings and equipment issues? Monitoring for such problems and catching them quickly is precisely what an inspection system can deliver. But more than that, having data that monitors when problems occur can highlight employee training needs that can save your operations time and money.
Big Data is Changing the Future, Starting Today
The best part of big data from an automated inspection and/or quality assurance system is that you will be grabbing data that is actually useful to your daily and monthly operations. Deriving the benefit of this new data requires only that you have systems that offer data tracking and that you have a plan to analyze the data. The first successes can be found in basics like determining a random failure versus a pattern of failures. Big data may seem like a huge lift, but the truth is when you boil it down properly, it will be better informed to make the same line operation decisions you currently make. Once you get those decisions ironed out, then you have the option to explore new areas you may never have considered before all this data was available. It is entirely up to you.
Take the first step, look at your manufacturing options for quality assurance and vision inspection systems. While asking about your options, be sure to ask for suggestions on how you can use all the big data that will pour into your hands. Now is the time to get into the big data game, before you get left behind. Big data is not just going to boom in the future, it is booming now. And tomorrow, it will start determining which manufacturers will grow and which will fall off into unsalvageable inefficiency.
Ready to make your manufacturing data matter? Check out Valco Melton’s ClearVision Systems: