While the future of manufacturing remains somewhat unpredictable, one thing is certain: companies will run more customized products in smaller lot sizes. And this will need to happen as manufacturers increase productivity and reduce costs.
What’s going on? Consumerism is the trend driving manufacturing in a new direction. The old-style make-to-stock model does not work in this environment. Seasons have become shorter, consumers demand regional styles, and more buyers look for unique items. Consumers are spending money on less-expensive, short-life consumables.
This trend does not mean consumers are willing to accept poor-quality products. On the contrary, they expect to receive value from goods being produced in an environmentally friendly way while also requiring social responsibility and transparency to be parts of the process.
Manufacturers will be challenged to manage material flow in this world of just-in-time manufacturing efficiently. And if they have not already done so, they will need to turn to data analytics very soon.
What is Material Flow?
Since products are created from materials, material flow is a critical factor in manufacturing. Companies cannot cover their costs until they sell their goods, making it essential to move the materials as quickly as possible.
Material flow is defined as the movement of raw materials, components, work-in-progress inventory, and final products through the production chain until it reaches the consumer. When it’s working properly, material flows predictably through the system. Of course, the rate of progress can fluctuate depending on changes in volume or unplanned interruptions in the process.
Why is Material Flow So Important?
Today’s smart factory saves money on storing, handling, and transporting costs when material flows smoothly. There is less waste and energy consumption, reducing the required floor space. Production times are shortened, while labor and resources are used more efficiently. The benefits of an effective material flow will show up on the bottom line.
However, beyond profits, enhanced material flow helps manufacturers comply with sustainability and transparency requirements, use increasingly scarce raw materials more efficiently, and reduce their carbon footprint.
Why is Material Flow Optimization Difficult?
Some manufacturing organizations continue to work in data silos. When you think about the various departments involved in material flow—production planners, managers, material planners, procurement, sales, and finance—it’s hard to imagine that each of these groups might have access to data that is not easily accessible by the other groups.
However, it’s not unusual for many manufacturers to find departments and teams working in their silos and making information sharing and collaboration difficult, if not impossible. And data that isn’t easy to find and use in real-time does not help the decision-making process, nor does it allow for a comprehensive overview.
Ensuring Smooth Material Flow with Data Analytics
Establishing the groundwork for improved end-to-end material flow is a substantial undertaking that’s well worth the effort. The following four stages should facilitate a smoother material flow and provide efficiency throughout the process.
1. Collect data and centralize it
Too many manufacturers have their departments operating separately, resulting in siloed data and the potential for substantial amounts of wasted time, and an increase in human error caused by poor communication. By enabling universal access to centralized data from the start of the production process, collection in a central location will break down these silos.
Tearing down the silos to enable universal access to data is an excellent starting point. For this to happen, organizations must collect data from every possible source – warehouses, sensors, ERPs, inventories, manufacturing execution systems (MES), and programmable controllers (PLCs) – as part of the entire process.
The collected information is stored in a centralized repository, such as a virtual data lake, to be accessed throughout the company.
2. Automate process monitoring
While centralized data is an excellent beginning, companies must use the data productively. Automated programs will help to detect abnormalities in the processes. By having continuous, automatic monitoring, along with rule-based notifications, manufacturers can ensure that the material flow goes as planned.
The programmed “rules” spot deviations in the process, including material shortages, bottlenecks, and work-in-process inventory overflows. When one of the rules detects that a limit has been exceeded, it automatically sends a red flag notifying operators to take corrective action preventing the bottleneck, storage overflow, or material shortage.
Automating monitoring and data analysis helps manufacturers discover why something has occurred much more quickly than any human could work out manually from the data.
3. Visualize current data
The use of technology gives operators and managers relevant and timely views of the material flow, allowing them to complete their jobs efficiently. With automated monitoring working in the background and ensuring the processes are under control, managers and operators can focus on the tasks at hand.
However, the volume of information generated makes it almost impossible to take it all in from raw data. Because human eyes can process visual cues faster than written text and numbers, visualization gives workers the tools to be more productive. Visuals help workers store and remember information longer. When they understand what the visual data means, it’s much easier for them to quickly recognize and grasp new data as it is updated in real-time.
Data visualization results from extracting pertinent information from large data sets, giving the entire organization beneficial insight into how different data sets are connected. Employees can quickly identify and extract patterns and trends otherwise concealed in the raw data.
4. Predict and be proactive
Data analytics enables technology to identify and anticipate logjams and overflows, allowing the workers to act swiftly to avoid a work stoppage. The first three steps helped create awareness of the material flow today. But in the future, you will want to know beforehand what will happen with the material flow.
Manufacturers need to be several steps ahead in the process to react to increases in production speed, decreases in batch size, and more frequent changeovers and deliver on time. To do this correctly requires Predictive Analytics and Machine Learning techniques to teach computers to spot glitches and data outliers that previously predicted an incident like a bottle-neck or storage overflow.
Applying these algorithms in the real-time data flow, manufacturers can anticipate problems and send out alerts earlier. In other words, companies will have the opportunity to act before the whole process has been affected.
The Benefits of Streamlined Material Flow Are Indisputable
The advantages of using data analysis to ensure a smoother material flow are numerous. It quickly identifies any issues in the informational and material flows while also pointing out ways to enhance them.
Because companies now have end-to-end visibility, they have eliminated the problems associated with data in isolated silos. These changes result in lower operating costs, improved operational efficiencies, reduced turnaround time, better quality, accurate inventories, and a boost to productivity.
In the future, the optimized material flow will provide more than profits. It will also help companies comply with more rigorous sustainability and transparency requirements. Manufacturers can reduce their carbon footprint and use increasingly scarce raw materials more efficiently, allowing them to run production with an eye toward sustainability.
About the Author: Eric Whitley has 30 years of experience in manufacturing, holding positions such as Total Productive Maintenance Champion for Autoliv ASP, an automotive safety system supplier that specializes in airbags and restraint systems. He is also an expert in lean and smart manufacturing practices and technologies. Over the years, Eric has worked with all sectors of industry including Food, Timber, Construction, Chemical and Automotive to name a few. Currently, he’s a part of the L2L team.