Why cloud analytics and remote monitoring are the future of automation

As technology changes the way employees work and the way they carry out their roles, Rockwell Automation’s Marc Baret presents five pitfalls businesses need to address in order to enable digital transformation

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Marc Baret

Automation is transforming the way employee approach their jobs, the locations of their employers and how the work they carry out is defined. Forrester predicted that one million knowledge-work jobs would be replaced by chatbots, software robotics, RPA and virtual agents in 2020. This may sound like an ominous forewarning, but the report also estimated that many jobs would be added to workforces, as roles will still require empathy, intuition and mental and physical agility.

The increase in automation adoption will bolster connectivity and reliability, helping businesses to make data, systems and processes more available and accessible. However, many manufacturing firms are finding their routes to automation and digital transformation strategies are slowing down productivity levels and increasing risk of downtime.

Addressing these concerns is possible through tools such as predictive analytics and maintenance that act as a virtual extension of their teams. However, implementing these technologies successfully requires additional external expertise. To explore this further, we present five pitfalls we see businesses face as they approach digital transformation and suggestions for how to address them.

Pitfall one: Cybersecurity risks

Security breaches continue to make major headlines due to the serious impact they can have on business. A breach not only risks a loss of sensitive information but also disruption, downtime and performance issues, as well as serious reputation damage. This highlights the importance for businesses to improve their data management processes and invest in their IT infrastructure.

Predictive maintenance support can help manufacturers avoid such issues by automatically monitoring for unusual patterns and immediately identify potential signs of data theft or network intrusion. They also require a comprehensive approach to security that includes policies and procedures and provides layers of defense around people, processes and technology risks.

Pitfall two: Having too much data

Businesses are generating huge volumes of data that, when utilized correctly, can be an immensely valuable asset. However, many manufacturing organizations don’t know how to make the best use of their data and, as a result, don’t optimize their workflows or production processes in a way that enables them to gather the best insights and results.

Being able to understand massive amounts of data is key to solving the biggest challenges facing organizations. But the skills and capabilities required to do it are rarely part of a business’ core competencies. It’s therefore important to partner with a trusted data expert that can collect the right information, store it and present it in a way that enables them to make the most effective business decisions.

Pitfall three: Poor management of data

Businesses are amassing more data than ever, but simply having huge amounts of data does not suffice. They need tools that help them better harness their data and understand the information they have.

The true value of automation lies in the IP that businesses hold on their customers, processes and product designs. Leveraging AI and machine learning enables them to analyze huge amounts of information, hypothesize and create significant data patterns, and train learning models to discover the unknown. Furthermore, data teams will be able to try more use cases in significantly reduced times, which will help them to make huge strides in understanding their data.

The potential of these advances in AI is highlighted by McKinsey analysis that found the most advanced deep learning techniques could account for up to $5.8 trillion in annual value. In two-thirds of the 400 use cases it tested, AI improved performance beyond that enabled by other analytics techniques. Without this ability to collect huge amounts of data from multiple platforms and action it effectively, manufacturers will continue to struggle to draw effective conclusions on changes and productivity within their plants.

Pitfall four: Not keeping up with the pace of technology

The amount of buzzwords surrounding digital transformation can often be overwhelming and even irritating for businesses that simply want technology to work. Many providers also demand vast investments upfront, which can be a daunting prospect and can put businesses off when a project doesn’t work out. Furthermore, getting locked into one vendor or deployment can result in companies getting left behind by their competitors.

It’s therefore important to work with providers that offer a pilot or prototype in advance of any deployment that represents a huge technological shift. This will provide a step-by-step vision of how the process will work, provide milestones, and help the business understand how it will work and what their expected ROI will be. Trusted technology partners need to be extensions of a team if they are to help businesses realize their goals and KPIs.

Pitfall five: Lacking expertise

Even with the right automation technologies in place, businesses often still require external support from people with appropriate experience and expertise. This can now be achieved by using augmented reality to provide remote application support and overlay information for engineers to follow.

As with any technology deployment, it needs to fit in with the business’ culture and what works best for their specific needs. However, businesses that are slow to move on these types of emerging technology run the real risk of being left behind.

Embrace the future of automation

Meeting the key challenges of better productivity and reduced downtime is possible with the right technology practices and the right technology partner in place. By understanding the common pitfalls outlined above, manufacturing firms can better navigate their path to the future of automation. However, digitalization is not something they can achieve alone.

Join Paolo Butti, Director Industry and OEM - EMEA at Rockwell Automation and Matthew Graves, Director of Connected Enterprise Consulting at Rockwell Automation on 1 July 2020 at 11:30AM BST, to discover how to stay ahead of your competition by implementing a smart, customer-centric, flexible manufacturing environment. Register for free to PEX Network’s upcoming webinar, How to achieve flexible manufacturing, and learn how to increase flexibility within manufacturing and how a machine-as-a-service approach can drive OPEX efficiencies.

This blog was original posted as The Future of Automation: Remote Monitoring and Cloud Analytics

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