The manufacturing industry is entering a new era where new forces created by the explosion of data, robotics, automation, and artificial intelligence (AI), amongst others, are changing the dynamics for manufacturing companies. Article by Stephen Las Marias.
To be successful in this new environment, manufacturers should consider a paradigm shift, focusing on innovation, integration of new technologies, and collaboration with their partners – and even with the competition – to build new solutions and take their production to the next level.
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And that’s where key transformative technologies such as big data, analytics and the Internet of Things (IoT) come in. Industry 4.0 – our nascent industrial generation – represents digitalisation across all operational processes. Industrial IoT (IIoT), in particular, describes an integrated system of systems where sensors and actuators provide specific data such as measurements, timing, and equipment status, all connected and visible throughout the enterprise.
In this scenario, we’ll see the convergence of operations technology (OT) in the factory floor with information technology (IT) in the enterprise, all working together towards a single purpose – a more-efficient, profitable and successful manufacturing operation. With IIoT, companies will be able to view real-time data on their manufacturing processes, and compare performance across their plants, or even shifts within their plants. They can also quickly scale their production up or down; manage their energy consumption; and even manage, troubleshoot and fix their processes and plants, even when they are located in different parts of the world.
Data is what’s powering this. Seamless exchange of data between automated machine processes, including manual assembly, and testing, to name a few, provides clear visibility of the operations of this ‘smart factory’.
According to Mariano Kimbara, senior industry analyst for the Industrial Group of Frost & Sullivan, data will be the new value-multiplier for the factory. “Factory owners will strive to network various aspects of a plant, such as tools, assets, material, people, process, and services, on one digital platform. The level of integration and collaboration will offer customers unprecedented information visibility and subsequently generate value from domains that were generative before,” he said.
Making Use Of Data
Data plays a key role in all of these. As manufacturers produce more and more sophisticated machines, with multiple sensors providing all the necessary data to ensure the health and performance of the machine, measurement, tracking, monitoring, inspection data – users today, on a daily basis, are grappling with more data than they ever did a decade ago.
With Cisco forecasting more than 50 billion connected devices by 2020, it is expected that there will be a deluge of data coming from these connected systems of systems. Which means a mindset shift is required when it comes to deciding what to do and how to leverage these data to improve your manufacturing operations.
Having all these data from your more sophisticated machines and tooling equipment is good, but the challenge is finding that relevant data that will provide you an actionable intelligence that you can implement to improve your processes.
According to Thomas Jakob of Bosch Software Innovations, this begins with sourcing for data creatively. He said companies can impel a more comprehensive look at information sources by being specific about problems they want to solve or opportunities they want to exploit. This means identifying and connecting the most important data for use in analytics, followed by a clean-up operation to synchronise and merge overlapping data, and then working around the missing information, according to him.
Once the information is in your hands, there are many ways how this will help you in your road to smart manufacturing. First is through preventive and predictive maintenance. Majority of the machines are now equipped with sensors that collect many different types of data, such as operating time and the conditions of the components and parts. Having these data provides users the knowledge on whether a part is no longer functioning efficiently and therefore needs replacement. Or, if a certain job is more tedious than the previous one, the machine will have to be rested for a slightly longer period than that required of the previous job. These things will help keep your metalworking equipment running efficiently, smoothly, and prevent machine downtime.
According to Bob Gill, general manager for Southeast Asia at ARC Advisory, the proportion of machine tool time actually taken up by cutting metal is generally less than 40 percent and can even be as low as 25 percent. He said that it can be difficult to accurately pinpoint the causes of all that non-productive machining time because most machine shops are performing manual, post-production data collection. In a smart factory, where your machines are constantly releasing production data, you will be able to gain intelligence on the impact of machine stops and tool changes in production, and as such plan more effectively and efficiently to improve machine uptime and utilisation.
Smart Data Leads To Smart Energy
Another benefit that you can get out of your smart data is energy usage. Smart machines provide data on their energy usage. Based on this, you will have the information when to ramp up production based on energy demand. Moreover, machines could power down when not in use.
And last but not least, quality control and assurance. With smart data, manufacturers will know whether a particular machine is not performing properly by comparing information about its performance to previous jobs. Or in case there are particular products that are not according to specs, users will be able to trace back where the process ‘faltered’, which resulted to production mistakes.
Industry 4.0 is here – and manufacturing operations can significantly benefit from utilising IIoT, smart data, and analytics. Building the right kind of technologies and expertise to apply them is critical for everyone to be competitive in this new industrial landscape.
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