Since the rise of computing in the 1960s and ‘70s, advancements in IT have been paralleled by developments in operational technology (OT). Yet, while manufacturing kept at the forefront of automation on the factory floor, it fell behind other sectors in digitising paper-based processes at the plant level. Companies may have deployed numerous systems – enterprise resource planning (ERP) and the like – to drive improvements, but many struggled to leverage the data collected in their manufacturing plants because it was such a large human undertaking.
Emergence of the internet of things (IoT) in the last decade, however, has accelerated their digital transformation journeys. New solutions incorporating advanced analytics have enabled manufacturers to identify and anticipate the failure of a machine based on data insights generated through the use of low-cost sensors and analytic programs that can interpret factors such as vibration, temperature or throughput. By being able to predict quality with IoT, and also to prescribe what to do through insights driven by artificial intelligence, the potential is there for manufacturing organisations to transform from a position of making improvements based on past learnings to being able to prepare proactively in the best way.
Despite the huge potential of IoT, many of the schemes thus far have been limited to pilot projects whereby manufacturers pick a certain problem area and concentrate on the technology required to solve specific issues. Typically that means putting sensors in and getting some IoT gateways. They’ll collect data, combine information from their ERP system and optimise processes to drive improvements. While this provides value to that individual use-case, the real challenge for a multinational company is standardising and spreading improvements across all sites.
“What is often lacking is the capability to capture the knowledge you’ve gained from that pilot in one individual plant and then extend it across multiple plants,” says Steve Garbrecht, technical product marketing director for IoT at Hitachi Vantara. “You want to take the best practices from one site and reinstitute them in another. There’s this need for scalability, but the experience and resources out there to do it are lacking. There are people who know OT technology, but they lack knowledge in how to institute some of the more advanced IT architectures to really take IT to the shop-floor environment.”
Hitachi Vantara is seeking to bridge the gap between IT and OT, bringing to manufacturing the production process benefits that Toyota, another Japanese giant, brought to the automotive industry. Hitachi is in the unique position of having vast experience in both OT, from 110 years as a manufacturer in its own right, and IT, when for 60 years it has developed data management architecture, products and solutions. The company creates systems for use within its own plants, but also the manufacturing plants of its customers.
We’re bringing OT and IT together, and it’s a really powerful combination
Earlier this year, Hitachi Omika Works, which manufactures automation control systems for industrial operations, was inducted into the World Economic Forum’s Global Lighthouse Network of advanced factories leading the way in applying Industry 4.0 technologies to drive efficiencies and operational impact. The Omika Works factory showcases Hitachi’s Lumada solutions, combining OT and IT technologies, and has reduced the lead time of core products by 50 per cent without impacting quality.
“We’re bringing OT and IT together, and it’s a really powerful combination,” says Garbrecht. “What the Japanese and Hitachi have found is that by being able to improve the processes, which include the people, materials, production processes and the approach from a manufacturing point of view, you can gain competitive step-changes within the marketplace. By making improvements overall within not just Hitachi but the industry and society as a whole, we can make things better for everybody. A rising tide raises all ships.”
Factories generate an enormous volume of captured production data which could be used to drive transformation, but 70 per cent of it goes unused today, according to the World Economic Forum. Until manufacturers adopt new practices to manage and derive insights from the data, and apply those insights to business outcomes, its potential will remain untapped.
Approaching data management and data analysis in a consistent way is imperative. Being able to compare results and operations from site to site requires data management at both the edge and the site factory-floor level, and all the way up the enterprise. There are two different groups using the data. On one side are the on-site operations and engineering teams that require visibility and a quick analysis capability of the data. On the other are data scientists, data engineers and IT people doing more advanced analytics and designing machine-learning models.
Between these two groups, manufacturers need a way to manage the data so it can be shared in a timely and correct way, or sometimes not shared at all if regulatory or security policies dictate so, or if it’s not worth the costs of transmitting and storing it in enterprise or public-cloud platforms. Manufacturers, therefore, need to be more curated at the local level to ensure data is cleansed, corrected and in a suitable format before it reaches the enterprise.
Traditionally, manufacturers look at four possible root causes of poor quality or performance on shop floors – man, machine, material and methods – and attempt to isolate problems to increase efficiency and productivity through continuous improvement. In the IoT age, they have the chance to digitise kaizen, the Japanese word for improvement, and adopt advanced technologies to generate insights that identify where particular defects in quality can be traced.
“Industry 4.0 is about bold changes that enable not just continuous improvements but real transformation,” says Sath Rao, director of digital solutions for manufacturing, industry solutions marketing, at Hitachi Vantara. “Leveraging a system of insights can drive transformative outcomes. Historically there’s been this monolithic legacy system of records and then islands of automation on the shop floor. What was missing is the focus on return on data. The fourth industrial revolution is all about the focus on cyber-physical systems that can drive business agility. Establishing the digital innovation foundation is core to accelerating the digital transformation journey.”
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