Companies need to transform themselves internally’
Published by : Industrial Automation
What is the kind of impact emerging technologies are having on industrial automation?
There is a positive and a negative impact on the industry. The positive one is that emerging technologies like Artificial Intelligence and IoT have made the processes more efficient and trackable. The insights have become real-time and managers are able to make quick decisions on the basis of that. IoT has helped managers monitor progress in real-time thus increasing operational efficiency, which is linked to improving the bottom line. Artificial intelligence, on the hand, predicts the health of the system thus helping managers replace or repair machines before the end life, or before the possibility of failure. This overall leads to using maximum production capacity. Complete autonomous processes have decreased the manufacturing cycle and thus leading to match the industry demand.
Now coming to the negative impact, due to emerging technologies, there is a hype in the industry on who uses a certain technology first. Thanks to the FOMO (Fear Of Missing Out) factor, CxOs are more concerned to showcase themselves as AI-enabled or IoT-enabled or Blockchain- enabled company without actually looking into the real use cases, which need their attention. This has caused concern since most of these projects are not linked to RoI and then they go in sunset mode. This leads to a negative mind-set FOMO2 (Fear Of Money Out) of the management before using the technologies next time and thus demotivates the research and development in such areas for genuine use cases.
How is Artificial Intelligence helping the cause of fully autonomous manufacturing?
Let me first set the context of what Artificial Intelligence (AI) is.
I always give an analogy of a baby while explaining Artificial Intelligence to anyone. Like a baby learns when exposed to a new environment and takes decisions on its own later, similarly AI also learns when more and more datasets and situations are given to it. To manufacture a product a set of tasks needs to be repeated multiple times with the same parameter and precision if parameter differs by a certain amount it can lead to wastage and loss. Automated machines are provided with the range in which they can work if they are out of range the machines usually stop the production or alerts or rectify itself.
When we put AI into such systems, the AI helps in understanding the pattern by collecting the data from such machines. AI tries to predict the failure or cause of concern by analysis. To make autonomous manufacturing possible AI should also be connected to the mobile repairing systems, which can repair the machines when there is a failure; or procure certain parts and replace them together. Sounds like movie Terminator, but it is a possibility and in some places,even self-healing materials are used, which can be repaired by machines on their own in case of something going wrong.
Despite the many advantages, there are trust issues when it comes to Cloud Computing. Are the fears exaggerated?
Cloud computing has evolved a long way. Cloud providers are providing their service through the internet. So if you have an in-house data centre which is connected to the internet then cloud computers or your internal data centre both have to face the same vulnerabilities. Having said that, cloud companies are constantly innovating and upgrading their security since they have the resources and bandwidth to do so. All top cloud companies are the best recruiters around the world. Since their core business is cloud computing they recruit the best talent possible to look after network and infrastructure security. Since a single breach in their security systems can affect their business to a lot extent. Compare this with the internal data centre. To maintain this we need a data centre operations team, do you think one can match the cloud provider standards of recruitment for that? The fears are exaggerated for cloud computing but vulnerability will remain since every new day new security threat comes up and this needs to be fixed as soon as possible for minimal impact. Also, new security frameworks need to be implemented which requires good skilled resources and a lot of costs to be spent on security patches. So, from the operational cost and maintenance of security, cloud computing is far better and secure.
Can technology like Blockchain reduce the inefficiencies in manufacturing operations, especially in the supply chain?
Blockchain is not a holy grail, blockchain is one of the most advanced technologies which is misunderstood because of the FOMO factor. Let us understand Blockchain first – in simple words it is an encrypted ledger of which copies are saved at different locations, which are connected to each other via the internet. Once there is an update in the ledger the systems having the ledger copy validate each other to check whether the change is authentic a kind of multi validation of a ledger. There are inefficiencies in manufacturing operations due to errors or disruption of the service. Blockchain system may not be helpful in this case. Blockchains can be used when there is a threat of manipulation retrospectively in records, it is similar to someone trying to erase the past ledger records. The blockchain-based system will not let that happenm since the records now are distributed and would require manipulating records at all places which is a bit a task. Also, Blockchain Smart Contracts help in creating programs which can help in transactions across multiple parties without any manipulation. This can help in the supply chain based payment systems where payment terms are defined and depend upon certain events.
Is the pace of technology too overwhelming for most enterprises, especially MSMEs?
Yes, it could be overwhelming to change so frequently and make changes so rapidly in a large enterprise but MSME needs to be agile. The biggest difference between a Large Enterprise and MSME is agility. Large enterprises adhere to strict processes since they cannot afford to make the smallest mistake since they are into delivering large projects whether it is manufacturing or services. But MSMEs can experiment and try new things to innovate. Once working, then they can scale up their work with the new innovation. So, MSME should welcome such speed and use it to their advantage.
What should be the roadmap companies should follow in adopting these technologies?
Firstly, companies need to transform themselves internally. Adoption of technologies needs a mind-set change. When such products are adopted the employees need to go through a learning curve. This needs an openness of the employees to learn especially in manufacturing. It gets a little difficult since most of the workers and supervisors are working on equipment which has been there for years. Secondly, the type of KPI’s changes. The way the data is perceived earlier and now will be totally different. Now a finer set of data is available which can be leveraged for new sets of KPIs and old KPIs may not be relevant.
Second, these are very new technologies, e.g., Artificial Intelligence cannot work from Day 1. It needs a sufficient amount of time and data points to make decisions or predict accurately relevant to your system. So patience is needed, these technologies work the best with time. Also, we need to understand that the ecosystem is also gearing up and it requires a bit of time to stabilise a system like these. So whether it's Edge Computing, AI, Blockchain, AR/VR or IoT, they are still evolving. So having patience is a virtue.
Third, Ecosystem Development – the mind-set of keeping things to oneself and proprietary to the company needs to change. The world is moving towards Open Source and technologies since that helps in building better products. Crowdsourcing information and technology helps an organisation tackle problems faster. Organisations should share information with companies and partners in the same sector so that sector flourishes and it helps the ecosystem better to learn about the technology and upgrade it further.
Adnyesh Dalpati is an Enterprise Architect, Technologist and an Internet of Things (IoT) Evangelist with 15+ years of experience working in Investment Banks, Stock Exchanges, Cloud Companies, Media Companies, and Telecom. He has held executive positions in JP Morgan, NSE and Alef Edge (US-based Edge Computing Company) and currently serving as Chief Technology Officer in 4 Marketing Technology.
Adnyesh has developed many low latencies, high performance and scalable solutions using nextgen technologies like Edge Computing, Marketing Technology, Artificial Intelligence (AI), Virtual & Augmented Reality (AR/VR) and Blockchain Technology Applications catering to domains in Telco, Finance, Logistics, Media and Retail. He also runs two social initiative – Eureka Moment and Storypedia – to motivate youth. An advocate of 4th Industrial Revolution and a member of various technology groups, he also speaks about next-gen technology and its use cases on his BrightTALK channel and conducts seminars, workshops on technology at various forums.