Compared to sectors such as finance, insurance, health, and retail, the capital-intensive industries have been considerably slower to embrace digital transformation. ARC Advisory Group (ARC) revealed that although more than 80% of industrial process manufacturers are piloting advanced technologies, only 5 to 8% are ready for digital transformation today.
The main barriers to adoption are organizational inertia and scalability of use cases and users, while the most significant driver in the industrial sector is the need to address the business consequences of unplanned downtime.
The Time is Now
While we all know that the best time to start was yesterday, the next best time is now. Craig Hayman, CEO of AVEVA, a leading global engineering and industrial software organization, believed that the most opportune time to take up the mantle of organization-wide digital transformation was now.
“It’s never been easier .. as cheap access to cloud computing, great connectivity, a merged edge and enterprise combined with analytics and machine learning means that the ability to digitally drive productivity improvements into the industrial world is now unprecedented.”
Besides, Hayman added that there was "no mystery to machine learning," and machines could quickly surpass a human in ingesting data. Pointing out that "moving quickly" was essential if companies wanted to maintain their competitive edge, he stressed on the many benefits of digital transformation.
The biggest is improved asset health, which Hayman saw as resulting in a reduction in unplanned downtime and better asset performance. Meanwhile, incident prediction capabilities will lower operational risk and protect worker safety. Also, cognitive learning can deliver digitized intelligence that will result in knowledge and experience being freely available throughout the organization.
3 Stops to DX Destination
AVEVA works as a partner to accelerate organizations on their digital journeys, helping them to accelerate digitalization, realize the value of digital twins, and build digital teams.
Hayman outlined three critical steps to a successful digital transformational journey.
Firstly, he urged organizations to ‘snap-in' a unified operating center to visualize industrial data they already had. Secondly, organizations need to use big data, analytics, and collaborative tools for smart asset performance management and build a knowledge profile about an asset. Machine learning and artificial intelligence can provide predictive and prescriptive mechanisms for operational efficiency. This should apply to the whole portfolio of global assets. Finally, organizations should bring simulation into engineering design and use the cloud to eliminate legacy workflows.
“Over time, these three steps combine into an end-to-end digital twin, that spans from an organization’s original engineering data through to operational performance and maintenance work,” said Hayman.
“By leveraging the integrated data and analytical capabilities of the individual digital twin, companies can embark on true digitalization to optimize their asset’s life-cycle. This process begins with the initial capital investments right through to the operating phase of a modern plant, refinery, or smart city.”
Start your Digital Engines
One such use case is with the China Ministry of Railways (MoR).
MoR needed to develop a high-speed line from Beijing to Tianjin within 18 months, integrating multiple hardware and software vendors into a Passenger Information System. The new system required effective integration with current equipment and infrastructure, and a user-friendly, economical operator interface.
A primary goal was to enable the centrally integrated facilities management system to support communications equipment, such as the public address system, video displays, automated ticket sales as well as closed-circuit television monitors and other components used by supervisors to manage operations and safety systems.
The AVEVA solution was chosen because it offered the advantage of off-the-shelf, object-oriented software that could scale quickly. It was also extendable to the entire train system of China.
The open architecture allowed the standardization required for easy development. It also enables redeployment of applications, promotes repeatability, supports customization, and saves time, thanks to the AVEVA application templates.
Before this, the MoR system was not integrated. This created inefficiencies in deployment, operations, and maintenance. The new system uses a centralized facilities management strategy using standardized technical architecture requirements and operations.
The fully integrated core system enables all status and control instructions to be shared automatically with the different railway stations, allowing comprehensive management of personnel according to demand, reducing operations costs. A systematic program has been developed to maintain the extensive railway system for optimal performance and upgrades. A portion of the station equipment is also automated to increase energy savings, while real-time station asset data is used for trending and more efficient reporting.
Currently, the 120 km Beijing-Tianjin line takes just 30 minutes to complete, saving travelers 40 minutes each way. The MoR has continued its digital transformation journey across the national railway system. It is currently the most extensive high-speed rail line in the world at 8,358 km with a centralized management core system that has successfully integrated 60 different third-party vendors.
The Passenger Information System is installed in 220 railway stations and 15 high-speed rail lines across China, using over 200,000 I/O points on 1,300 platforms.
The expansion will continue into 2020, where the AVEVA solution will help MoR manage an estimated 3 million I/O points. According to MoR, return on investment is expected within 6 years.