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 quality. What is new? The way in which the Internet of Things promises to take smart factory 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 connected factory is creating unimaginable possibilities for quality improvement, using the IoT to build bridges that help solve the old problems of frustrating disconnectedness among suppliers, employees, customers and more. In doing so, 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.
Read an e-book by LNS Research
Quality improvement is one of the top use cases for Industry 4.0. Download the Quality 4.0 Impact and Strategy Handbook to read about the tools and insights needed to lead the Quality 4.0 transformation.
Download the free e-book
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 moving so quickly that spreadsheets and human analysis alone are not enough to manage them. Companies need advanced analytics to process the vast amounts of data being created via smart sensors and the IoT, and even more agile processes to integrate the data and 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. But now, the global digital 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 faster, more agile and efficient model for product delivery is 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, reducing warranty costs.1 And that’s now. Imagine what the benefits will be as IoT continues to expand.
If you’re still not sold on the smart factory, consider this: Embracing the IoT can help your company in three major ways, enabling you to:
- Produce a higher quality product.
- Improve your internal production processes.
- Enhance customer experience (CX).
Smart factories allow companies to stream data in real time, gleaning insights that allow on-the-spot changes in source materials, machine functionality and even customer service. Daniel Newman CEO, BMG & Principal Analyst Futurum Research
A better product
In the past, by the time companies ran reports, collected information from various factory floor stations and tallied data from customer service, the effects of subpar quality had already been felt throughout the customer base. In other words, the damage had already been done. IoT in manufacturing changes all of that. Smart factories allow companies to stream data in real time, gleaning insights that 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 could save in lost products, 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 be taught to self-correct to fix that defect before additional errors occur. That’s right: With the gift of artificial intelligence, machines can do jobs humans alone used to manage. And they can do it in near-real time. That leads 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. That’s something no company can afford in today’s marketplace.
Sensors in the smart factory setting give manufacturers the ability to automatically monitor wear and tear in real time. Machine learning can 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 could 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 offline 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.
As I’ve said before, CX is the heart of digital transformation.2 And nothing aids customer experience better than consistent quality. When customers know they can always rely 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 analyzing the data that smart sensors capture while products are being used in customers’ homes, manufacturers can get a better sense of when or if products fail, how they’re being used and how to adjust the manufacturing experience accordingly. Using advanced analytics, they can also 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 for the smart factory is now
According to a McKinsey report, the potential value of the IoT in factory settings could hit nearly $4 trillion by 2025.3 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.
How do you know if your company is ready for the smart factory? For one, you’ll need to be willing to invest in IoT analytics technology – preferably technology with strong data visualization capabilities to help your teams understand and process the data. In fact, there’s almost no point in adopting IoT technology if you don’t have analytics 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-driven decisions. If your IT, HR and floor teams aren’t well-versed on the capabilities of the IoT, make time to educate them.
Building a smarter factory might take a culture shift at some levels of the organizations. But from where I stand, it’s a shift worth making.
Join me and my co-host Brian Fanzo on SMACtalk as we speak with Marcia Walker of SAS about smart factories and how IoT and analytics have created a massive opportunity to maximize productivity and minimize downtime.
About the Author
Daniel Newman is the Principal Analyst of Futurum Research and the CEO of Broadsuite Media Group. He works with the world’s largest technology brands exploring digital transformation and how it influences the enterprise. He is regularly cited in CIO.Com, CIO Review, CNBC and hundreds of other sites across the world. A five-time best-selling author, including Building Dragons: Digital Transformation in the Experience Economy, Newman is also a Forbes, Entrepreneur and Huffington Post contributor, and a graduate adjunct professor.
- Article Continuous monitoring: Stop procurement fraud, waste and abuse nowProcurement fraud, waste and abuse silently robs businesses an average of 5% of spend annually. And even when organizations invest in detection methods, they’re often let down by their techniques. Learn what continuous monitoring is and why this proven analytical method is key to fighting back.
- Article How health care leaders deployed analytics when crisis hitDuring the COVID-19 pandemic, some health care providers were well-positioned to respond to rapid changes in demand. The factor that most distinguished them was that they already had a strong capacity in place for using data to inform decisions. Read about three key takeaways from their experiences.
- Article ModelOps: How to operationalize the model life cycleModelOps is where analytical models are cycled from the data science team to the IT production team in a regular cadence of deployment and updates. In the race to realizing value from AI models, it’s a winning ingredient that only a few companies are using.
- Article 薄酒萊如何新鮮準時送到你手中？酒莊用AI預測供需 退貨減80% 時序入冬，迎來法國的薄酒萊產季，每年11月第三個週四，是薄酒萊新酒全球同步上市的日子，全世界的人們都能一起舉杯品嚐，歡慶年度盛宴。為了不讓葡萄酒供不應求，美國葡萄酒酒莊開始運用AI分析，提高消費者需求預測的準確度。