Want a Robot but Don’t Know Where to Start?

Mitsubishi Electric

Industrial or collaborative? This is the question everyone is asking. We all want to get the most out of our production, however the demarcation line between the two options is not as clear as you might think. It all depends on the setting in which the machine operates, how operators need to interact with the robot and its main functions.

Barry Weller, Solutions Marketing Manager – OEM at Mitsubishi Electric, looks at how to identify what type of robot is best suited for your application and how to integrate it.

The first question that companies interested in automating their processes should ask is: what do we want to achieve? The answer to this will determine the role and type of robot needed. Consequently, conducting a comprehensive risk assessment will shed light on the safety requirements.

For example, if speeding up operations is the main objective behind deploying a robotic solution, conventional industrial robots, such as Mitsubishi Electric’s MELFA RV articulated arm and RH series SCARA robots, are quite likely to be the most suitable option. As the application will dictate, these robots move at high speed which means they are suitable for applications where workspace is to be shared with human operators only by adopting additional safety provisions. The options to integrate them are to construct physical safety perimeter guards or implement systems that allow automated speed control when humans approach the robot working area.

Conversely, if the main goal is assisting employees in their activities, for example by passing or holding parts, the application would be considered collaborative. As a result, any conventional physical separation between humans and robots would obstruct the application. In this case, the ISO/TS 15066:2016 standard supports the development of suitable safety measures, as highlighted by the risk assessment. An example of a robot designed for collaborative applications is Mitsubishi Electric’s MELFA RV series Assista articulated arm robot.

The guidelines indicate different types of collaborative applications which include safety-rated monitored stop, speed and separation monitoring, hand guiding as well as power and force limiting.

This is where the grey area between the two types of robot starts to appear. With the increase in safety options now available, industrial robots can also achieve many of the requirements needed in a collaborative application.

Industrial or collaborative robot?

Designed to work alongside humans collaborative robots or ‘cobots’, can provide a safe solution. However, there are some obvious caveats.

The term collaborative, as specified by ISO/TS 15066:2016, actually refers to systems or applications where automatically operated robots share the same workspace with humans. This means that robots for collaborative applications, just like any other type of robot, still require a risk assessment.

There are different industrial operations whose risk assessment would support the use of cobots, for example, if the robot is required to work alongside the human as part of the assembly process to pass objects to operators. Here the risk of a collision between the two is high and so this application would fall into the category of power and force limiting. Features such as safe torque range to detect the impact and prevent injury are needed.

There are situations where the use of robots would require additional safety measures. For example, if potentially harmful chemicals, sharp edges or extremely hot items need to be handled, the robot would need to be enclosed by physical safety perimeter guards to protect human operators. Because of this, the use of a conventional robot is likely to be the right choice for these applications.

In other situations humans may need to infrequently enter a robot’s workspace to briefly interact with the application or there could be a limited area of interaction. These systems will run as fast as possible under normal operation and only slow down when there is a risk of collision. Again this would suggest that a conventional industrial robot would be right for this application due to its ability to operate at high speeds in normal safe operating conditions.

As suggested, the most effective way to make such applications fast, safe and reliable would be to utilise standard industrial robots operating in a cooperative way, coupled with additional safety features such as physical guards or safety light curtains and scanners.

More precisely, businesses can implement high-speed, high-payload industrial robots, such as the MELFA RV articulated arm robot, equipped with a MELFA SafePlus safety system from Mitsubishi Electric. This means humans and robots can work safely and in harmony.

Making the right choice

As technology evolves, the line between industrial and collaborative robotic applications also changes. The most important consideration when implementing a robotic system is to ensure the system meets the needs of the specific application and delivers against the user requirement specification. The system must achieve both the throughput required and also operate in a safe environment for operators in line with the risk assessment for the application.

The inclusion of collaborative robots has widened the choice and the type of applications that robotics can now be used for. It is not a question of which is best, industrial or collaborative robotics but which is best for the application. With its wealth of experience and proven track record, the robotics team at Mitsubishi Electric helps businesses find the right solution.

Thanks for reading!

Like what you read? This article was published by Mitsubishi Electric. For more information go to www.mitsubishielectric.com

Making IIoT and Smart Technology happen

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Applying new technology to a physical process or manufacturing system is an essential part of progress, however the practical side of implementing the latest Industrial Internet of Things (IIoT) and Smart Technology solutions is bringing its own unique challenges. That in turn is leading to new automation solutions.

Chris Evans – Marketing and Operations Group Manager of Mitsubishi Electric UK looks at the latest challenges and solutions.

When looking to develop and install new smart manufacturing systems at an existing location one of the most important pieces of groundwork that needs to be carried out is to fully understand what the organisation is trying to achieve and what are their immediate “pinch points?” In addition for an existing location, what is the level of automation and infrastructure that already exists and what needs to be added to create a bridge between the operational technology (OT) & the information technology (IT) levels in the organisation. This vertical integration of a factory or plant has machines with automation on one side and the enterprise level on the other and it is the ability to gather information and bridge this OT/IT gap which will ultimately create the opportunity to become a smart manufacturing operation.

Communication Standards

As already mentioned, to enable IT and OT integration there must also be horizontal connectivity at the shop floor level, i.e. between machines from different suppliers with disparate automation vendor’s equipment and different elements of plant control. Therefore, the openness of the automation technologies being used plays a key role; communication standards need to be used that will “speak” to all machines, sensors, actuators and other components. Evaluating the current level of automation and network infrastructure is critical in understanding what will be possible in the short, medium and long term and how easy or difficult it will be to match the goals of the organisation in becoming a smart operation. The good news is that whatever level an organisation is currently at, with good project planning and communication the journey towards digitalisation and smart manufacturing can be achieved to the appropriate level for the organisation in question.

Adoption of standards for machine control and network connectivity has further aided the process, for example in the food & beverage and packaging industry, organisations are frequently operating in a multi-vendor automation machine environment and are now using developments in the OMAC PackML and OPC UA standards to achieve better integration.

Talking heads

In the past the IT and OT worlds have not been natural bed fellows with the OT world operating in real time with process speeds of milliseconds or below and the IT world operating at much longer sampling times, such minutes, hours or more. There has been a natural divide between these two worlds but the advent of Edge computing technology to sit in the “space” between the two has made the integration of these seemingly diverse worlds much more straight forward and allowed a greater level of choice about where data analysis takes place.

It is easy to assume that if the necessary levels of automation and network infrastructure on plant either already exists or now exists as phase one of our plan to become smart, the natural extension of this is to collect every byte of data that it is possible to collect and sit back and admire what has been achieved.

Of course it needs to be more scientific than that. Inevitably, increased communication in recording those machine ‘conversations’ will create the need to manage a far higher volume of data. This requires the creation of a platform for efficient data analytics and data transfer between the OT and IT levels. The challenge is to handle all that data in a structured way, filtering out unnecessary “noise” and turning “Data” into “Information”. 

Performing Analysis on Data

Not losing sight of our goal to become a smart manufacturing plant, performing analysis on this data will allow us to visualise the important aspects of production: Overall Equipment Effectiveness, productivity, quality control, use of raw materials, waste and predictive and preventative maintenance, all of which are familiar to production directors tasked with making the operation more efficient. The question is often “where best to implement our data analytics?” Is it best to move everything to enterprise level servers or even the cloud, or is there an alternative? 

Edge Computing

Of course the new smart technology appearing at the “Edge” not only gives an alternative but greater flexibility and efficiency of data management. Edge computing offers industrialised solutions designed to live in the plant environment like all other automation equipment and to be at the “sharp end” of the data collection process. As previously discussed, the IT and OT worlds are often divided by the frequency at which data is sampled but Edge solutions offer the chance to perform sophisticated data analysis incorporating recognised AI algorithms in real time and therefore interface with the plant automation systems at high speed, making machine learning and improved production efficiencies a reality.

The next major benefit to carrying out data analytics at the Edge layer, is that the data can be filtered and only the necessary and relevant data passed to the enterprise or cloud based servers. This can considerably reduce the cost of data processing at this level, where cost is often attributed to the number of data points processed. It is clear that by linking the IT and OT world, the Edge classification of technology is playing a key role.

MELIPC Edge-Computing Solution

Into this space, Mitsubishi Electric has launched the MELIPC Edge-Computing solution: The MELIPC solution takes care of all connectivity issues “downstream” to the plant level, supporting all of the major open networks and removing the problem of interfacing to machines or plant assets controlled by disparate automation vendors. It provides a real time data logging and processing environment in a ruggedized industrial form factor. From a data processing perspective, it incorporates a suite of analytical tools such as; multiple regression analysis, the Mahalanobis-Taguchi system and Statistical Process Control (SPC) and AI functionality such as Similar Waveform Recognition, giving responses to process analysis in real time. 

Mitsubishi Electric’s MELIPC Edge solution provides open connectivity, a suite of analytical tools and AI functionality, giving responses to process analysis in real time.

MELIPC has a dual operating system of Windows and VxWorks RTOS which gives the user the flexibility of embedding third party applications into either of these environments. The VxWorks RTOS environment has a proven track record of running critical embedded applications where high availability is a mandatory requirement. The internal structure of MELIPC follows the Edgecross framework as defined by the Edgecross Consortium which is an independent organisation of over 200 members whose goal put simply is to standardise the interface between the OT and IT layers.

In the final analysis

One of the biggest challenges faced by manufacturing industry is to ensure that final product quality remains consistent, independently of variable environmental conditions, raw products and in-feed ingredients.

Many plants have “optimised” their operations but what digitalisation and the road to smart manufacturing offers in addition to this, is the ability to move to a predictive model based on a continuous improvement strategy and if this is followed to its ultimate conclusion then the whole plant eco system including energy supply and the supply of raw materials can be completely integrated and made operationally efficient. The seamless vertical connectivity between OT and IT also opens up manufacturing industry to newer business models – like ‘batch size one’ or the rapid changeover of one product line to another to keep pace with fast moving consumer trends. 

One of the key takeaways from this march of change, in systems, technology and networking is that it can be applied equally to existing production lines and equipment as it can for new factories. Manufacturing by its nature is now a mature industry, so upgrades and progress inevitably involve managing change, not just for physical plant and software layers but for people too. 

All manufacturing plants have the capability to become smart operations, the journey to that goal may be short or long but can be achieved step by step with the right planning, required investment and partnering with the right automation vendor to help plot and navigate the course.

Predictive Maintenance Can See The End of Unplanned Downtime for Food and Beverage Companies

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With any unscheduled downtime being a cause of major headaches for food and drink manufacturers, John Rowley of Mitsubishi Electric highlights how predictive maintenance can provide the solution and how easy it is to implement.

With food manufacturers being continually squeezed on price by retailers and asked to fulfil orders for supply that can seem, at best, challenging and at worst highly unrealistic, improving productivity is a priority. Tight timescales mean many lines are already running on a near 24/7 basis, leaving little leeway even for scheduled maintenance, let alone an unexpected breakdown. This can lead to overcautious service and maintenance regimes, which are expensive to support, but preferable to unscheduled downtime which is the worst possible scenario.

Short supply or delayed delivery due to plant failure damages a business’s reputation and impacts on the relationship with the customer. And as many food and beverage manufacturers find to their cost, customers such as supermarkets can’t support empty shelves, which makes them very demanding customers indeed.

How to avoid grinding to a halt

Let’s not forget as well, that many production line failures are not characterised by a sudden fault that results in immediate line stoppage. Often it is a gradual degradation that impacts on product output. That means before the line eventually grinds to a halt, it might have spent a considerable period producing inconsistent goods – that add to the bottom-line cost of the issue, due to waste.

So we can see that both unscheduled downtime and the developing causes of that downtime both impact directly on productivity, with a direct link to increased costs. The impact of unpredictable downtime is endured right across the food and beverage industry.

The good news is that random equipment failure – leading to unscheduled, emergency repair – doesn’t have to be a fact of life. Modern condition monitoring sensor technology can be easily retrofitted to rotating plant and equipment, while many of today’s plant and machine controllers have advanced monitoring and diagnostics functions built in, ready to use.

Taking advantage of these technologies can quickly take food and beverage companies into the realm of predictive maintenance, where businesses can see advanced warning of impending equipment failure, with enough time to plan repairs during scheduled maintenance periods rather than being hit with an asset failure out of the blue.

Mitsubishi Electric’s SCM kit provides an integrated approach to monitoring the condition of individual assets and enables a holistic approach to be taken to monitoring the asset health of the whole plant.

Evolving from preventative to predictive maintenance

A conceptual and technological leap forwards from preventative maintenance, intelligent predictive maintenance ensures an asset is serviced only when needed, not based on routine helping to increase both productivity and efficiency. Predictive maintenance spots equipment problems as they emerge and develop, providing ample warning of impending failure, and so helping to maximise asset availability. They also help combat inadvertent neglect; humans are generally very smart, but not 100% of the time, and situations change, as do staff, taking knowledge built-up over years with them.

Importantly, these predictive maintenance solutions are not complex; frequently they are simple and cost-effective to implement, and often they can be built from functions that already exist within the plant’s control equipment.

Take, for example, the add-on sensors that have been developed to monitor the increases in operating temperature, excessive current draw, changes in vibration characteristics and significant shifts in other operating parameters that can all be indicative of impending problems in rotating machines. Today these sensors come with embedded ‘smart’ functionality, revolutionising condition monitoring.

A simple add-on to pumps, motors, gearboxes, fans and more, these sensors used a simple traffic light system of red, amber and green lights to provide at-a-glance monitoring of the condition of the machine. In addition to this they can also be connected into wider factory automation networks using Ethernet and a managing PLC for a smarter solution.

From traffic lights to telemetry

In isolation sensors offer a great start point to implementing preventative maintenance strategies, but of course there are limitations to the traffic light warning system. While it indicates that a problem is developing, it gives no real clue as to what the problem might be or just how serious it is; it offers no practical recommendations as to how the problem should be addressed; and while it shows problems developing on individual machines, it fails to provide an overview on the asset health of the plant.

It is these limitations that Mitsubishi Electric has addressed with the Smart Condition Monitoring (SCM) solution. The kit provides an integrated approach to monitoring the condition of individual assets and enables a holistic approach to be taken to monitoring the asset health of the whole plant. Individual sensors retain the traffic light system for local warning indication at the machine, but at the same time information from multiple sensors is transferred over Ethernet to a Mitsubishi Electric PLC for in-depth monitoring and more detailed analysis.

The SCM kit provides a plug-and-play solution for machine condition monitoring. Sensors can be added to machines as and where required, with a simple teach function allowing the sensor and controller to learn the normal operating state of the machine, generating a memory map of key parameters. Once set up, the SCM provides 24/7 monitoring of each asset, with functions including bearing defect detection, imbalance detection, misalignment detection, temperature measurement, cavitation detection, phase failure recognition and resonance frequency detection.

Linking multiple sensors into the control system enables the controller to analyse patterns of operation that are outside the norm, with a series of alarm conditions that can provide alerts when attention is needed. The SCM analysis provides detailed diagnostics, offers suggestions for where additional measurements should be taken, and provides maintenance staff more precise error identification. It can even make recommendations as to what rectification actions should be taken, with clear text messages presented to personnel. Further, this information can be networked to higher-level systems for ongoing trend analysis across all the assets around the plant.

Muntons Malt demonstrates how it should be done

Looking at a practical example of the technology in action, Muntons Malt, one of the UK’s largest producers of malted barley is reaping the benefits of the SCM system to protect fans and motors vital to its large-scale and sensitive production process. The operation team had previously experienced issues with difficult-to-reach bearings inside a large fan housing, realising too late that a problem existed, and was forced to make an unscheduled stop to one of the lines to make repairs.

Determined to learn from this, Muntons Malt installed the SCM system on two large 315kW fan sets and a single 90kW fan set, referencing the electric motor, power transmission coupling and main fan shaft bearing on each. The company is now extremely conscious of the health of the fan sets and has a very clear picture of any maintenance way in advance of needing to make physical alternatives. Remote monitoring and fast diagnosis of any issues has also made the company very reactive should the operating parameters that have been set, even be approached.

Muntons Malt, one of the UK’s largest producers of malted barley is reaping the benefits of the SCM system to protect fans and motors vital to it’s large-scale and sensitive production process.

With the technology, live information and any alarms are displayed on a GOT Series HMI mounted in the control enclosure. The system can work autonomously of any other automation, with multiple sensors located and recognised by unique IP addresses. However, at Muntons Malt the visual information as well as the alerts were connected into the existing automation software platform.

This ease of connectivity illustrates further advantages of today’s condition monitoring technologies, which can provide immediate, visible alarms anywhere in the world on smart devices. For multi-site businesses, this can aid in quickly changing over production schedules from one plant to another to fulfil the most pressing orders or can alert remote maintenance teams of the need to perform more detailed diagnostics.

The information might already be in your drives

This information isn’t just coming from external sensors. Modern drives, PLCs, SCADA systems and other automation products have comprehensive diagnostics capabilities inbuilt, monitoring not only their internal workings but also parameters such as current draw, voltage & temperature in connected motors, pumps, & fans. All of this helps to build a detailed picture of the health of plant assets.

And with a simple plant network backbone, this information can be shared around the plant and beyond. Indeed, this sort of functionality is a key aspect of Industry 4.0 and is at the heart of the benefits of the digitalisation of production.

We can see, then, that predictive maintenance strategies can offer comprehensive analysis on the health of individual machines as well as a holistic overview on the health of the wider plant. The result is vastly improved scheduled maintenance and optimised asset lifecycle management. With maintenance able to be planned in-advance, there is far less unscheduled downtime and significant reductions in the loss of service at short notice. Also when assets are serviced only when needed, food and beverage producers can benefit from increased productivity and efficiency, with a very real impact on the bottom line.