Automation in manufacturing is nothing new. In fact, it’s been around for nearly 200 years—changing the face of how we make our products and ensure product quality. What isnew? The way in which the Internet of Things (IoT) promises to take automation to a whole new level by intelligently connecting all phases of the product life-cycle, from sourcing to delivery, and right into the customer’s home.
The IoT’s promise for manufacturing has been called “the fourth industrial revolution” or “Industry 4.0” for short. The new smart factory is creating unimaginable possibilities for quality improvement, using the IoT to build bridges that help solve the old problems of frustrating disconnectedness amongst suppliers, employees, customers, and more. In so doing, it’s creating a cohesive manufacturing environment where every employee feels invested in product quality—and every customer’s feedback is valued and learned from.
Smart Factories: Why Now?
With the complexity of the modern supply chain exploding—and real-time expectations of customers rising—manufacturers need more control over their manufacturing process than ever before. The only problem: the many pieces of the manufacturing puzzle are now moving so quickly that spreadsheets and human analysis alone are not enough to manage them. Companies need machine learning to process the vast amounts of data being created via smart sensors and the IoT—and even more agile processes to keep up with the pace of customer demand.
Indeed, in the past, manufacturing was a linear process. Products moved through the factory—and the greater supply chain—in a clear, straightforward manner. Now, however, the digital global marketplace has changed all of that. Companies are making products on-demand, sourcing numerous suppliers from around the world, and managing customer feedback via social media before their customer service representatives ever hear the complaint. It makes sense that a new, faster, more agile model for product delivery would be needed—and the IoT is the perfect tool to deliver it.
Yes, even the thought of implementing a smarter factory environment can be overwhelming. But it is worthwhile—and likely necessary—if you want your business to thrive in the digital marketplace. For instance, one factory found that while producing air conditioners with a fully-automated production line, 3-D scanners, and IoT technology, it could reduce lead times and costs, while also reducing the number of defective products by 50 percent. And that’s now. Imagine what the benefits will be the more IoT continues to expand.
If you’re still not sold, consider this: using the IoT can help your company in three major ways: by producing a higher quality product; by improving your internal production processes; and by enhancing customer experience (CX). I’ll explain how below.
A Better Product
In the past, by the time companies ran reports, collected information from the various stations of the factory floor, and tallied data from customer service, the effects of sub-par quality had already been felt throughout the customer base. In other words: the damage had already been done. But the IoT changes all of that. It allows companies to stream data in real-time, gleaning insights that can allow on-the-spot changes in source materials, machine functionality, and even customer service.
Smart sensors, for instance, can ensure that every item—be it an article of clothing or a top-secret defense weapon—has the exact same quality level as the one before. Imagine how many millions of dollars this can save in lost product, customer complaints, and damage to your company’s brand.
In fact, the beautiful thing about IoT in manufacturing is that once a defect is found, the machine can self-correct to fix that defect before additional errors occur. That’s right: with the gift of artificial intelligence, the machines can do jobs humans alone used to manage—in real-time. That lead to better products—and fewer losses—all around.
A Smarter Process
It’s impossible to keep a trained eye on every piece of equipment and machinery within the manufacturing sphere. Yet, nothing causes a major loss like dealing with unscheduled maintenance. Not only do companies feel the hit in lost production, they also lose in employee productivity, something no company can afford in today’s marketplace.
Sensors within the smart factory setting offer manufacturers the ability to automatically monitor wear and tear in real time. Leaders can use machine learning to create precise models unique to each process that can track time-to-replacement for parts and machinery. For example, if the cutting blades in a paper factory dull slightly, it may create a ragged edge that consumers dislike—one that may take several reams for a human inspector to catch. Predictive maintenance can help schedule blade replacement before that error ever occurs. Even better, it can schedule the replacement for off-line hours so no production time is ever lost. This in turn increases the overall agility of the company—which is what digital transformation is all about.
Happier Customers
As I’ve said before, CX is the heart of digital transformation. And nothing aids CX better than consistent quality. When customers know they always relay on your brand to deliver the quality they need and expect, they come back to you. That’s what the power of the IoT can deliver.
Still, production is just one part of the equation. By using smart sensors to capture data while products are in use in customer homes, manufacturers can get a better sense of when or if products fail, how they are being used, and how to adjust the manufacturing experience accordingly. Using machine learning and AI, they can also help quickly process public-facing comments made on social media about their products so they can tend to customer complaints in near-real time. If that isn’t empowerment, I don’t know what is.
The Need is Now
According to one McKinsey report, The Internet of Things: Mapping the Value Beyond the Hype, the potential value of the IoT in factory settings could hit nearly $4 trillion by 2025. Some estimate it could add $15 trillion to the world economy by 2030. Waiting to jump aboard the smart factory train will only leave today’s companies in the dust.
But how do you know if your company is ready? For one, you’ll need to be willing to invest in IoT analytics technology—preferably technology with high data visualization power to help your teams understand and process the data. In fact, there is almost no use in adopting IoT technology if you don’t have analytic power to help you process the data it creates.
And last, you’ll need talent. After all, the factory workers of tomorrow are not the same as the factory workers of 1820. Today’s automation is based on high-powered, real-time machines operating on complex analytics and making quick, data-informed decisions. If your IT, HR, and floor teams aren’t well-versed on the IoT and its capabilities, make time to prepare them.
Building a smarter factory might take a culture shift at some levels of the organizations. But from where I stand, it is a shift worth making.
This article was first published on SAS.com
Daniel Newman is the Principal Analyst of Futurum Research and the CEO of Broadsuite Media Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise. From Big Data to IoT to Cloud Computing, Newman makes the connections between business, people and tech that are required for companies to benefit most from their technology projects, which leads to his ideas regularly being cited in CIO.Com, CIO Review and hundreds of other sites across the world. A 5x Best Selling Author including his most recent “Building Dragons: Digital Transformation in the Experience Economy,” Daniel is also a Forbes, Entrepreneur and Huffington Post Contributor. MBA and Graduate Adjunct Professor, Daniel Newman is a Chicago Native and his speaking takes him around the world each year as he shares his vision of the role technology will play in our future.