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But that ultimate goal can seem a long way from what we frequently see today, with operators walking up and down a production line with a clipboard and a stopwatch. Omron’s Dan Rossek looks at the steps in between, and at how machine builders can develop machines that will help end users reap the benefits of continuous improvement.
The concept of marginal gains in productivity is nothing new. Through the 1990s, the buzzword in every plant and factory was Kaizen, with its focus on continuous improvement. This was soon combined with the concept of Lean Manufacturing, taking continuous improvement even further. And as we arrived in the 21st Century, we all started talking about the steps we could take to boost our overall equipment effectiveness (OEE) scores, first making the big, obvious changes but following that up by addressing ever-smaller production issues to keep delivering marginal gains.
Whatever the name, the focus of all of these strategies and processes is the optimisation of systems. Traditionally we have looked at optimisation from a perspective of individual production lines, and within that the picture has moved from one of individual operators making manual adjustments based on gut feel or looking at mean time before failure (MTBF) to one of improvements driven by analysis of actual production data.
Analysis of historic production data can reveal much about a given line, highlighting for example how bottlenecks always seem to happen at a particular time, or how a seemingly random stoppage actually follows a predictable pattern. Modern condition monitoring technologies have moved the downtime picture from unscheduled maintenance to preventative maintenance to one of predictive maintenance.
But can we go further? How close are we to being able to make improvements in real time, rather than based on analysis of last week’s data? Can we extend this plant-wide and beyond to really make an impact on the bottom line? And could we really see the paradigm one day where lines will self-optimise based not only on the plant’s operations but also on supply and demand requirements through the entire logistics chain?
These might seem like huge steps, but the key is data – how we collect it and how we use it. Indeed, a key premise of Industry 4.0 is the ability to refine processes based on data. Interestingly, no matter how far away the ultimate goals of Industry 4.0 may seem, the truth is that we are already much closer than we might dare to imagine.
Modern automation systems are capable of generating huge amounts of data, from the humblest sensor to the most advanced controller, and through all aspects of control including motion, drives, robotics, vision and integrated safety. Today’s automation systems integrate all of these key areas and let us take a holistic view of the plant’s operations. And they let us make the link with higher-level business systems in order to close the loop between logistics supply, production capability and customer demand.
It is easy to see how so many industries are finding themselves entering the realm of ‘Big Data’, but generating and collecting data shouldn’t be the start and end of the story. For machine optimisation, what we are looking for is not big data, but smart data – information that will allow processes to be continually refined.
With smart data, users can drill down into the operations of the machine in a way they never could have previously, uncovering far greater opportunities for optimisation. The result is significantly improved product quality (moving from quality control to quality assurance), improved productivity, increased efficiency (including energy efficiency) and increased machine availability (as predictive maintenance reduces downtime). And most importantly, we can begin to optimise processes in real time rather than making improvements based on historic data.
So how does the machine builder deliver on all of this for the end user? It might at first look seem like a huge implication for configuration and programming, but automation vendors have been busy developing their products with optimisation in mind. Automation platforms – such as Omron’s Sysmac platform – encompass the full range of control products from PLCs through to HMIs, drives, motion, robotics, vision and integrated safety, all on a single open network (with open possibilities for third party products) to enable a free flow of data at machine level.
Further, while device level fieldbuses have long provided a simple means of getting status data from sensors and actuators, new protocols such as I/O-Link are providing greater levels of information and diagnostics data right down to the edge of the network. At the same time, integration with standard database technologies such as SQL, means all of that information can be readily transferred to higher-level systems.
With this increased level of integration and greater amounts of meaningful data coming from machines and processes, machine builders can give their end users the ability to drill much deeper into their processes, getting far clearer indications of inefficiencies, production problems, impending component failures, maintenance requirements, and more. Data can be analysed in real time either at database level or locally to the process, and appropriate information can be provided for operators, maintenance staff and production personnel.
The importance of a unified automation platform such as Sysmac lies not just in the ease of moving data around, but also in the ease of programming to get at appropriate data and to turn it into meaningful information. Where software development time was once a barrier to implementing such functionality, today with a single unified programming environment for all aspects of control and the use of standardised function blocks, machine builders can significantly reduce development times, and easily deliver the high levels of information analysis that will enable smart decisions to be made, in real time. Where implementing such levels of monitoring and analysis might once have been a secondary consideration, they can now be offered as standard without any impact on development time, giving machine builders a significant competitive advantage.
From smart machines to smart factories
So where might all of this lead? Smart machines lead to smart factories, and that is what the concept of Industry 4.0 is all about. Smart machines recognise the importance of the operator as part of the optimisation process, arming that operator with appropriate information. Smart factories integrate multiple production lines, allowing bigger picture optimisation decisions to be taken – for example re-routing production according to status or bottlenecks or demand.
As we move towards the ultimate picture of Industry 4.0, using the same information we can begin to see machines and processes starting to take their own optimisation decisions. We can already see the beginning of how this might look in the latest generation of service robots for the plant floor. AGVs – which needed tracks, infrastructure and clear step-by-step programs to follow – are being superseded by autonomous indoor vehicles (AIVs) which are inherently self-optimising. If an AGV can be conceptualised as a train, then the AIV is more like a taxi service, easily deployed when and where it’s needed.
Imagine similar levels of self-optimisation replicated across machines, factories and even different plant locations – potentially in different countries, enabling manufacturers to optimise not just individual plants but complete global manufacturing operations.
That future is coming, but as we have seen a lot of it is here already, and Omron is helping machine builders and their end users take huge steps along the path. All of this capability comes as standard within the Omron product portfolio, so even complex functionality can be delivered as a matter of course by machine builders as it no longer needs to be considered as a barrier to machine development. Machine builders have it within their grasp to demonstrate to their end users how significant gains in efficiencies can be realised. And even marginal gains can have a big impact on the bottom line.
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