Demystifying Industry 4.0
Credit to Author: Constantine Lau| Date: Tue, 03 Dec 2019 15:56:56 +0000
This blog is co-authored with:
Rajesh D. Sharma is Global Marketing Director for the Schneider Electric Oil, Gas and Petrochemicals segment, and is responsible for developing strategy around Integrated Digitized Solutions (integrating Automation, IoT, analytics, Big Data solutions) and new business models for the Schneider Electric Oil & Gas portfolio of offerings. Rajesh previously acted as Managing Director for Telvent Energia SA branch, Abu Dhabi for the Middle East region and as General Manager in Reliance Industries, India where he was responsible for design and selection of control systems in midstream business. He holds bachelor’s degree in Instrumentation Engineering from India.
Industry 4.0 is the biggest enabler of business transformation that can bring big benefits for organizations that adopt it. However, there are many myths surrounding Industry 4.0 due to which companies are slow to take decision to move forward with digital transformation.
Let’s try to demystify a few of such common myths:
Myth: Systems are becoming more complicated to handle
The fact is that industry has been working on standards and processes to make systems simpler and more open. The efforts of companies like ExxonMobil and Saudi Aramco towards Open Process Automation Standards is yet another step towards making process control systems simple, moving from proprietary hardware design towards more open platforms. Tools available in automation systems are now able to use ‘plug and play’ features to configure common devices, eliminating human errors.
Myth: More data makes it difficult for users to focus on key performance indicators.
It is true that we are seeing more and more data being created with newer sensors and newer devices across the operations of oil & gas businesses. The data, however, is actually augmenting already existing data available in the facility. This new data adds insight into the performance of a process and helps to improve the key performance indicators. An example will be to add power meters to large electrical equipment. With such data, the operations team can schedule the operations of large equipment to lower the cost of operations. Another example would be integrating electrical data with process data, this would help in rapid and comprehensive diagnostics and predictive maintenance. Analytics performed at the edge help in consolidating critical asset information where it is really required, at the site. Assets are managed more efficiently, decreasing unscheduled downtime and increasing production.
Myth: Digital transformation requires changes in all aspects of business operations all at once
Yes, changes in all aspects of business are needed, but you can pace them according to the organization’s needs. For example, if you want to decrease unscheduled downtime and ensure health of all assets, it’s imperative to have asset performance management system with predictive analytics. However, you may have to add new sensors to devices which are not being monitored. Adding newer devices and newer sensors enables companies to create larger data lakes, but that is just an enabler for digital transformation. Having asset management does not warrant to have advanced process control or supply chain analytics at the same time, though these will also improve the overall efficiency of the particular installation. As put by Gartner, Digital transformation is “the process of exploiting digital technologies and supporting capabilities to create a robust new business model.” The key here is “new business model”, which refers to changes which a company must make in the way it conducts business. Integrating power and process is once such change which oil & gas companies are ready to implement as the benefits are clear.
Myth: Newer technologies will eliminate jobs
Jobs which are repetitive and mechanical in nature will be replaced by computers. This simply means that humans will have jobs which effectively use their skills and not just use them as robots.
Subject matter experts, operations experts, petroleum engineers, geologists, the list of job opportunities will remain same even when industry moves to increase automation across the business. Newer technologies such as immersive training and augmented reality, in fact, will enable knowledge transfer from experienced workforce to the new generation workforce entering the industry. Also, technologies like 5G will make remote data transfer easier and faster eliminating the need of time consuming and unsafe site visits.
Myth: My data can be compromised on cloud. This is somewhere between myth and reality
If the solutions selected are not cyber security compliant and if the proper architecture is not selected, there could be data breach. Having said that, the companies adopting digital transformation are fast learning the risks and mitigation methods of putting data on the cloud. Some companies go for private cloud while others go for public cloud, having completed due diligence of such architecture.
Myth: Artificial Intelligence (AI) and big data analytics can solve all complex problems
AI and big data are some of the key technologies in driving digital transformation but it is also important to start with the right domain knowledge to approach the business problems that we are trying to solve, for example understanding of the oil and gas industry knowledge in order to solve an oil field or plant process and equipment problems. The idea of AI originated in the 1950’s, but a number of advancements helped renew progress in AI like Moore’s law, cloud, big data, new algorithms etc. We saw major Improvements in processing speed (days vs minutes) and the economics (lower cost servers) of deploying AI solutions. However, the accuracy of the AI prediction output also depends on the accuracy of the input data, so it is important to start with the right domain knowledge.
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