Innovation

What the IIoT means for manufacturing

19 April 2017 by Tony Field

The Industrial Internet of Things (IIoT) is set to change the face of manufacturing as we know it. Tony Field, senior director, Social Innovation Business, at Hitachi Data Systems Asia Pacific weighs in. 

Tony Field, senior director, Social Innovation Business, at Hitachi Data Systems Asia Pacific

Digitalization is disrupting many industries like never before. How do you see digitalization (particularly the Industrial Internet of Things) impacting a traditional industry such as manufacturing?

Many industries are already benefiting from digitalization & IoT, and industrial manufacturing is actually leading the way.  The ability to “sensorize” everything and extract data to provide business insights is a huge benefit for manufacturing.  Several global studies are showing that industrial manufacturing will see the largest revenue increase compared with all other industries, driven by IoT.

For manufacturing, it will ultimately be about personalization. The ability for customers to directly configure and customize the products being offered and manufactured. This will require flexibility across the entire supply chain, new business models, new routes to market that provide a personalized service to customers rather than simply just a standard range of products sold via traditional markets.

The impact of this on manufacturing is that it will likely become event-driven rather than today’s process, which is typically built around a planned set of production runs.

In your view, how critical is it for manufacturers to start adopting IIoT in their processes? And what are the advantages of them doing so?

To ignore IIoT is to put the future of your business at risk, and manufacturing companies are already taking advantage of IoT today.  

Let’s look at one advantage - predictive maintenance. Today, a manufacturer may typically schedule preventative maintenance based on estimates of failures, whether maintenance needs to be performed or not. This causes unnecessary downtime and has labor and parts costs. But by being able to leverage sensors and analytics, we can now schedule maintenance based on actual usage prior to a part failing – this is predictive maintenance, as opposed to preventative maintenance. This impact is we can maximize production runs and reduce cost. Manufacturers of the actual equipment could also monetize this data and offer this “as a service” therefore providing new revenue streams.

Experts have purported the many benefits of leveraging IIOT technologies and data analytics in manufacturing operations. Can you describe some recent businesses which have undergone a positive transformational journey in IIOT manufacturing?

The best example is to look at what we have done ourselves. Hitachi’s Omika Works supplies information and control systems deals with high-mix low volume products that are customized to suit specific customer requirements and applications.

We were faced with ever-changing customer demands that put workers under pressure with unexpected orders and rescheduling work at the last minute. Along with RFID and other sensors to track actual production progress, we optimized the overall plant by improving coordination between departments, between processes, and between management and the workplace to create dynamic scheduling which improved overall productivity by 8 percent.

Another example was with a global manufacturer. The company’s polymer mixing process was producing output of inconsistent quality, with yields sometimes dipping as low as 50 or 60 percent. The scrapping of poor batches created huge costs and was crippling production capacity. The root cause was traced to ever-changing product specifications, in addition to variations in a range of production parameters.

We delivered an advanced analytics platform that integrated a wide range of production data and sensor data outputs to visualize, analyse, and diagnose the mixing process. This new insight enabled the production engineering team to understand the correlations and cause-and-effect from a wide number of variables.

The solution eliminated over 50 percent of the poor-quality batches, increasing the average yields to above 90 percent. Not only have the process parameters been optimized, but the system is now capable of continuously adapting to changing conditions. Additional benefits include:  a significant reduction in operating costs (millions of dollars); increased mixing capacity with higher overall production throughput; and flexibility to accommodate changing product designs, increasing numbers of product variations, and new or changing ingredients

What are typically the challenges manufacturers will face in driving an effective digital transformation? And what advice would you give manufacturers looking to embark on a digital transformation journey?

The biggest challenge when it comes to IIOT is building that business case. There are a vast number of technology options available out there today - hence it is important to work with experienced partners on how these technologies might be applied to the business, and whether it makes sense financially. Time spent on developing an executable business plan will ensure you deliver on the outcomes you expect.

As part of that digital transformation journey,  firms need to have support from the top. If the CEO is not embracing data and analytics as the way forward, effective digital transformation will fail.

Second, for Industrial IOT, find a business partner that understands the operational technologies together with IT technologies.  At Hitachi, we have over 100 years of operational technology experience and over 50 years of IT experience. That’s why we are able to bring together IT and OT to deliver IIoT.  Manufacturers and all industries need to leverage these types of capabilities and partnerships to deliver effective returns.

Third, and an often-overlooked aspect is to know your data. Like any organization, if you don’t have good data governance today, you will not be able to gain business insight. It’s the old saying -garbage in, garbage out. 

With a wide variety of opportunities that data-driven technologies present, manufacturers are pressured to decide what IIoT technologies will give them the greatest ROI. How would you advise manufacturers to initiate their IIOT strategies?

Start small and understand the business problem you are trying to solve – don’t get hung up on the technologies. Form a business analytics team - this will provide the focal point and governance where business problems can be submitted and evaluated in order to demonstrate the potential ROI and importantly, work with a known IT/OT business partner.

From there, manufacturing transformation is a journey that starts with digitization - digitize your assets and collect all the data into a “Data Lake”. The next step is analytics that enable factory personnel to gain better insights into operations. Advanced analytics via machine learning and Artificial Intelligence (AI) can also be implemented. Finally, Virtualization, which is the ultimate goal: this is where a “Digital twin” is created that lets production personnel run simulations on digital replicas of factories and equipment to improve flexibility and efficiency.

Last but not least, to simplify the approach to IIoT, utilize a IOT platform that is open, adaptable and secure. The message is, don’t get caught with a point IIoT solution that operates in only one silo of your business - implement a platform that can scale across your entire business.

Any other parting words for manufacturers?

The evidence is in front of you. IIoT for manufacturing is a reality today - don’t be left behind.

Edited by Liew Hanqing and Tan Yi Xuan