There are several pain points in modern manufacturing that can potentially be addressed with new technologies. What, then, are some of the best ways that modern manufacturing companies — sometimes called Smart Manufacturing or Industry 4.0 — can increase profits?

Pain Points In Modern Manufacturing

There are a variety of pain points that manufacturing companies face today: 

1. Labor: From pandemics to an aging workforce, it can be difficult for manufacturers to find and retain skilled workers.
2. Quality: In order to maintain a high level of product quality, manufacturers must have a robust quality control process in place. AI and machine learning can be used to analyze large amounts of data to identify patterns and anomalies, helping to identify potential quality issues before they become problems.
3. Supply chain challenges: The parts you needed don’t arrive in time, stopping a production line. Or the food product you received was contaminated by being stored near an allergen, leading to a costly recall. Having visibility along the supply chain is critical.
4. Inefficiencies: Why is your line slow? Is it a machine that needs maintenance, is broken, or is just old? The operator? Missing supplies? What efficiencies can you look at improving?
5. Maintenance & break downs: Maintaining equipment and machinery is a critical part of the manufacturing process, but often we don’t know when to proactively maintain our equipment? Or we wait until it’s broken, which slows production. What if we could know in advance, and use off-hours to maintain, before things broke?
6. Blind Spots: How do you know what you don’t know? Manufacturing without a clear picture of your entire process, from vendor to delivery, makes it impossible to truly manage and increase profits in your manufacturing business.

How can we address each point? The first step is to make sure you’re getting at least basic data from each component in your manufacturing process.

Get Your Machines Talking

Have you ever experienced an infant that is really unhappy and can’t talk? That might be a good analogy for some of our manufacturing equipment.

But then think about once that infant could finally communicate … at least a little. If you know they were hungry or tired, life was much easier. The same is true with manufacturing equipment.

So we need to get our equipment “talking” — we need that data.

Many manufacturers are still effectively blind to a staggering percentage of events on the factory floor. Yet most modern equipment has sensors. Some of the machines even have connections to the internet. And even without either solution, there are new ways — look at ThinkIQ Vision — to capture data even from analog projects and hand work.

Smart manufacturers are connecting those machines to the internet, and gathering that data. Devices that have a connection to the internet are referred to as the Internet of Things (IoT), and there were an estimated 20 billion devices, growing rapidly, connected to the internet in 2020.

The Internet of Things (IoT) has the potential to transform manufacturing operations and increase profits in several ways: 

1. Predictive maintenance: IoT sensors on machinery and equipment can help monitor their performance and predict when maintenance will be needed. This leads to increased production and reduced maintenance costs.
2. Real-time monitoring and control: IoT devices can be used to monitor production processes in real-time, providing valuable insights into operations. With analysis or context, this information can be used to identify bottlenecks, improve production processes, and increase efficiency.
3. Supply chain visibility: To some degree, IoT devices can be used to track materials, components, and finished products throughout the supply chain.
4. Energy efficiency: IoT sensors can be used to monitor energy usage, identifying areas where energy can be saved.
5. Improved product quality: IoT devices can be used to monitor production processes and identify potential quality issues before they become problems.

But is this everything we really need to know about our manufacturing process? Not yet.

Find Out What Happens Before And After Your Warehouse

Our machines are talking. But what about the things that happen before and after our product — inbound raw materials, shipping to the client, etc? How can we really have a full picture of our process without that data?
The solution comes in the form of supply chain traceability. Supply chain traceability involves the integration of multiple technologies. Some common methods for implementing supply chain traceability include:

1. Electronic Data Interchange (EDI): Exchanging business data electronically using EDI, means you could have immediate visibility into supplier and partner data.
2. Barcodes: The use of unique barcodes, scanned at various stages of the supply chain, allows you to track the movement of components and products.
3. Radio-frequency identification (RFID): It’s easy to attach RFID devices to products in your supply chain. These then communicate between a tag attached to a product and a reader. They can be read at a distance, and multiple tags can be read at once, making RFID an efficient method for tracking large numbers of products in real-time.
4. Other External Data: Whether it’s sensors or IoT devices at a vendor, or a connection to weather data, you can “see” externally to improve supply chain visibility and enable better decision-making.

 Just about any manufacturer could agree that all this data is amazing, in theory. But the reality is that it often becomes data overload — too many data streams in too many places in too many formats, to be ideal.

Understand What They Are Saying

Getting our machines to “talk” provides some significant benefits, as does having some insight into our supply chain. But once we have the data, we need to truly understand it — to give our data context.

Contextualizing IoT data makes it easier to identify patterns, trends, and insights, which can inform better decision-making. By combining IoT data with other data sources, such as production schedules, inventory levels, and machine performance data, manufacturers can gain a more comprehensive understanding of their operations and make more informed decisions.

With contextualized IoT data, manufacturers can truly find the inefficiencies in their production processes and optimize their operations, leading to reduced production costs, faster production times, and improved product quality.

Contextualizing your data — for example, combining it with other data source such as weather data and historical production data — also reduces risks, from equipment failures to weather issues around the world that disrupt your supply chain here.

By making sense of the vast amount of data generated by your manufacturing devices, you’ll gain valuable insights into your operations … and boost profits.

Blind Spots Or Visibility?

Manufacturing is radically transforming. Digital data is supercharging some manufacturers, while it just may leave others behind, unable to compete.

This transformation, from “old school” manufacturing to Smart Manufacturing or Industry 4.0 can can seem complicated, but there is a very specific path that can be followed: get data from our devices, get external data, and understand (contextualize) that data.

At that point, we have systems that can warn us well in advance of potential supply chain disruptions. They can tell us when to maintain our equipment. They can help us avoid recalls. They can even tell us how to optimize our onion cutting, saving 7% in raw materials costs for a major food manufacturer.

Industry 4.0 / Smart Manufacturing isn’t just another trend. It’s the key to remaining a competitive manufacturer in the years ahead.

 There is a clear path to Transformational Intelligence — Reach out to a ThinkIQ expert today to start transforming your enterprise with our advanced AI-driven solutions. You can also download our new eBook, “Using Computer Vision to Fill Manufacturing and Warehousing Blind Spots with Actionable Data” to learn more about how to gain greater visibility into your manufacturing process.