machine learning – Industrial Automation Review – Industrial Automation | Automation Magazine | Manufacturing Automation News & Resource https://industrialautomationreview.com Online Portal on Industrial Automation & Instrumentation Tue, 16 May 2023 11:04:52 +0000 en-US hourly 1 https://wordpress.org/?v=5.5.14 YASKAWA – Your partner in industrial automation excellence https://industrialautomationreview.com/yaskawa-your-partner-in-industrial-automation-excellence/ https://industrialautomationreview.com/yaskawa-your-partner-in-industrial-automation-excellence/#respond Tue, 16 May 2023 11:04:52 +0000 https://industrialautomationreview.com/?p=4448

Q. Could you give us an overview of Yaskawa and its eminence in cutting edge technologies related to automation? Yaskawa is a trusted global leader in drives, motion control and robotics and is continuously focused towards powering the best-in-class automation with its inventive and cutting-edge technology and ground-breaking innovations. We push the boundaries of technology […]

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Q. Could you give us an overview of Yaskawa and its eminence in cutting edge technologies related to automation?

Yaskawa is a trusted global leader in drives, motion control and robotics and is continuously focused towards powering the best-in-class automation with its inventive and cutting-edge technology and ground-breaking innovations. We push the boundaries of technology and our broad range of expertise in diverse industries enhances our ability to develop production ready and easy- to-implement systems. Since 1980, YASKAWA India has demonstrated a passion for automation by developing specialized solutions to help customers increase efficiency, improve quality, boost productivity, and deliver outstanding return on investment.

Our core strength includes providing turnkey solutions for Arc Welding, Press Handling, Machine Tending, Vision System and End-of-line Automation. At the Technology Centre in Japan, our main objective is to innovate, build and enhance YASKAWA products and software ecosystem, making technologies better for next generation of industrial automation and smart factories.
While the automotive market is demanding high speed technology and Ultra-low spatter welding, Yaskawa is offering MOTOPAC WL300 plus. We have Sigma-7 series servo motor which makes high speed and synchronous welding wire feed control possible. Additionally, we also offer handling robot series which range from 0.5 kg to 600 kg payload which will find varieties of applications in the automotive & non-automotive industries. With Industrial robots, Motion Control and AC drives, we have indeed figured out the challenges which will be faced by the industries in future with an idea to meet customer requirements.

Q. What is your niche and standing in robotics?

We majorly deal in applications like arc welding, spot welding, handling, pick, pack and palletizing, foundry, forging, painting and many more. With over 150+ robotic variants, we have been able to successfully accomplish 9000+ Robots installations in India. The desire for continuous evolution and improvement to meet customer requirements has made YASKAWA develop and offer smart adaptive technological solutions for various industries. Our renowned and esteemed customer base spread across various industry segments including automotive, machine tools, FMCG, electronics, packaging, healthcare, textile, steel, cement, oil & gas etc. and we have been serving to the big two-wheeler, three-wheeler and four-wheeler OEMs and their tier-1 and Tier-2 suppliers.
We rely on giving our customers the best possible solution and reducing proximity. Today with operations spanning over the length and breadth of the country, Yaskawa India provides robust business support with complete nationwide coverage through a network of 10 regional offices and 50 authorized business partners and services across India. We have the robust capabilities to stand in the market reach and diverse nature of marketing activities. YASKAWA along with its partners established the centers of excellence of robotics and automation in various engineering institutions to develop skills in the work force and in future generations.

To continue accelerating innovation in a period of rising manufacturing complexity and its subsequent automation need, we take pride to announce the opening of our new state-of-the-art robot solution facility that aims to take industrial robotic automation to a new level.

Located in the heart of industrial cluster of Manesar, Haryana, the state-of-the-art Experience Centre’s proximity to customers will enable closer collaboration and accelerated development of solutions for the full range of industrial robotic applications offered by Yaskawa.

Q. You seem to have done some 9000 + installations hitherto. Which are the key industries and applications you cater to?

Flexibility, mobility, and collaboration are leading the way for robotic automation implementation in this era. With the rapid change in technology, consumer demand and competitive pressure, we are surely trying to work on the best possible access for the customer. YASKAWA is the largest producer of Industrial robots with over 150+ robotic variants and have been able to supply and successfully integrate 9000+ installations in both production and specific process cells.

We have expanded the lineup of our Motoman GP series for handling applications, SP series for spot welding application and PH series for handling between press processes to be in the latest trend in robotic automation. We also have a YRC1000 micro small size Robot controller and Motoman HC Series collaborative Robots, which clearly make teaching easy.

Our installations are clearly a huge success starting from healthcare to manufacturing plants, entertainment parks, commercial establishments and core Industries including automotive, machine tools, FMCG, electronics, packaging, and life sciences. We as a pioneer in these sectors, always strive to optimize the productivity and efficiency of machines and industrial systems with our innovations.

We hold expertise in various applications such as Arc & Spot Welding, Deburring, Buffing, Glue Dispensing, Handling (loading/unloading components in CNC machines), Picking, Packing and Palletizing applications with Cutting Edge technology. Our robots are the world’s fastest robots patented till date designed to maximize the performance and are best in the industry in the range of speed and working envelope.

YASKAWA - Your partner in industrial automation excellence

Q. How do you substantiate the statement that you are a total Solution company?

Starting our journey of PLC in the 1980 and AC drives in the 1990 to heading on Robotics application in 2005, YASKAWA India always believes in spreading its wings with each passing decade. We clearly have focused on innovations. The solution concept of i3 mechatronics (integrated, intelligent, innovative) with Yaskawa-cockpit, AC Drives, Servo Motors & machine controllers, robotics System engineering to designing equipment for energy saving and creation, we have mastered it all. Our current Robot product range gives customers flexibility to choose product payload from 0.5 kg to 800 kg with the reach of 0.35m to 4m for Arc, Spot, handling, Press automation, painting, and work with collaborative requirement YRC1000 controller.

As a “Total Solution Company”, we contribute to the development of industry and society through fusion of core technological advancements & open innovation and help organizations address their toughest challenges today and achieving endorsing success in future. Our products and solutions have been supporting automation in additive manufacturing, building automation, water and pumping, packaging, food and beverage, material handling, machine tools, oil, gas and petroleum, rubber & plastics, elevators & escalators, electrics, automotive, mining, iron & steel, textile,
pulp & rubber, and cement industries.

We are serving everything necessary to support the promise we have always made. Heading up with the idea of intelligence, integration, innovating new products and enhancing the existing one, we are relying on being a total solution company, but there is still a long way to go.

YASKAWA - Your partner in industrial automation excellence

Q. What is the latest trend in robotic automation?

With industry 4.0/5.0 fully taking shape, the trend in robotic automation keeps on going radical transforms. Artificial intelligence (AI), machine learning (ML), the internet of things (IoT) and big data are driving robots into most aspect of everyday life coming in the top latest robotic automations. In response to the current trends,Yaskawa is promoting i3-mechatronics as a solution Concept for realizing a new Industrial automation revolution with the introduction of Yaskawa cockpit which is a three-dimensional (integrated, intelligent, innovative) digital data solution and provides real time visualization of the status, health, and performance of your device.

Every year the trend in the sector keeps on transitioning for small and medium sized enterprises and particular industrial robots and Cobots are playing an increasingly important role in new areas of process, production, and handling. The trend in robotic automation is greatly affected by IoT and AI these days and with the help of automation techniques, Yaskawa has developed servo motors, ac drives, industrial robots, Yaskawa cockpit and smart factory solutions which help to maximize productivity.

Yaskawa Electric was the first to put forward the concept of Mechatronics, which is now widely used and accepted and has helped with the latest enhancements.

Q. You also offer human collaborative robots. What places your cobots in a class apart?

Yaskawa Motoman HC Series has significantly brought in the spectrum for Human-Robot-Collaboration application.

A payload of 10-30 kg combined with the maximum working range of 1900 mm permit flexible use in a variety of applications. It gives effective support particularly with physically demanding tasks such as palletizing of large card boxes or other stackable goods. It also lifts heavy loads improving workplace ergonomics.

Due to its dust and drip-proof protective glass, the Cobots also prevail in harsh environments such as machine loading where the robot often comes into contact with cooling emulsions. The high lifting capacity permits the simultaneous handling of several heavy workpieces with the double gripper that is a standard of CNC automation. The use of Food grade lubricating grease makes it suitable for the food and chemical industries giving it a user-friendly operation. YASKAWA human-collaborative robots are a new generation Robotics that is capable, affordable, versatile, simple to use and built with the industrial strength for which Yaskawa products are known. These robots are for customers looking for easy automation that can work in close-proximity to humans.

YASKAWA - Your partner in industrial automation excellence

Q. Please throw some light on your manufacturing excellence and quality obsession?

Yaskawa’s sophisticated technology has been built up over a long period of 100+ years history. It has been embodied in the form of various products and making great contributions in society. Those technologies or products are built through steady efforts of our predecessors though the process up to the present was not an easy one.

Regardless of the advancements that have taken place over time, Yaskawa’s commitment to quality has never changed. At Yaskawa, we are constantly trying to outperform our benchmarks, with a continuous focus on R&D. We have always been known to set the standard for quality which competitors strive for. Our patents for the world’s fastest robot are amongst many significant achievements, which demonstrates that we place quality innovations first. All our products are genuinely 100% tested under full current making our failure rate lowest in the industry. After the manufacturing is done, the products go through a few processes to ensure maximum quality viz. Quality through continuous improvement, Total quality management, Certified vendor program, and Product certification process.

Q. How is the demand pattern for robotics for industrial application in India? What are the stimuli and how do you expect the market to grow?

Industrial robots are in operation around the country and have become an indispensable equipment for production of automobiles, home appliances, PCs, Smartphones, and other products that are now a part of everyday life. Robotic industries are leading the industrial application with 48% (approx.) of annual installations per year. The demand for industrial robots from general manufacturing industries is anticipated to pick up at a healthy rate over the forecast period. Industry 4.0 has played a pivotal role in propelling the demand for industrial Robotics in India and as a stimulus Yaskawa is promoting i3-mechatronics, artificial intelligence as a solution Concept for releasing a new industrial automation revolution.

Our industrial robots are the core products to realize this concept and are used in a wide range of industries including electric and electronic equipment, semiconductor manufacturing, biomedical, food, medical products, logistics and are continued further. After the announcement of first MOTOMAN in 1977, we have shipped 540,000+ units all over the world. We develop servo motors which are the main component of industrial robots and aside from controlling software technology that maximizes this capability, we also develop industrial robots by integrating application technology that realizes optimum structure and function for applications such as painting and welding.

Much dependence on robots could be observed in the coming year in the industrial sector as they give proper reliability, accuracy and speed. Reports suggest that industrial robots worldwide could reach 20 million by 2030 taking over automated workers.

YASKAWA - Your partner in industrial automation excellence

Q. What is your vision for Yaskawa India?

At YASKAWA India, we tried to establish a corporate structure and management base being more local, adopting a DNA of Yaskawa culture that enables us to take innovative actions to realize our vision 2025.

Yaskawa has embraced industry 4.0/5.0 and its technology to carve a bright future of Indian manufacturing and we have redefined our vision as the automation and optimization of factories through i3-mechatronics and new field of mechatronics application for sustainable development. Through the Yaskawa cockpit, we are heading towards the goal of a data management system as a step towards the realization of the i3-mechatronics solution.

We work on strengthening management foundation that contributes to sustainable society and business by sustainable and productive manufacturing, create a rewarding workplace and human resource development, fair and transparent governance system. With AI, robotic automation, big data, IoT and machine learning we are analyzing the current process with all big data, and filling the gaps related to it.

Yaskawa believes that its technology can contribute to solving business challenges. With an aim to offer Eco mechatronics for the people of the earth, Yaskawa makes effort in research and development with its long-cultivated mechatronics technology into the next generation mechatronics that can widely contribute to social development. Our mission 2025 clearly focuses on leveraging the pursuit of our business to contribute to the advancement of society and the well-being of humankind which clearly aim to improve the quality of life empowering innovation and delivering results.

 

 

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WHAT IS RPA? WHAT IS INTELLIGENT AUTOMATION? A COMPLETE LIST OF AUTOMATION TERMINOLOGY https://industrialautomationreview.com/what-is-rpa-intelligent-automation-complete-list-automation-terminology/ https://industrialautomationreview.com/what-is-rpa-intelligent-automation-complete-list-automation-terminology/#respond Wed, 20 Nov 2019 09:07:58 +0000 https://industrialautomationreview.com/?p=1782 RPA

Not sure what the latest automation acronym means? You’re not alone. The shortening of terms to an abbreviation of letters is meant to make things simpler, but we are all aware it often doesn’t .For anyone stepping into a room of people from an industry which they aren’t part of, it can feel like they […]

The post WHAT IS RPA? WHAT IS INTELLIGENT AUTOMATION? A COMPLETE LIST OF AUTOMATION TERMINOLOGY appeared first on Industrial Automation Review – Industrial Automation | Automation Magazine | Manufacturing Automation News & Resource.

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RPA

Not sure what the latest automation acronym means?

You’re not alone.

The shortening of terms to an abbreviation of letters is meant to make things simpler, but we are all aware it often doesn’t .For anyone stepping into a room of people from an industry which they aren’t part of, it can feel like they are speaking an alien language.And, as automation is part of the tech industry — which is probably more guilty than most for creating swathes of acronyms — we have been known to throw one or two into a conversation.

SO, WHAT IS RPA? GETTING TO GRIPS WITH THE DIFFERENT AUTOMATION PROCESS TERMINOLOGY ON YOUR OWN TERMS

Of course, in any purchasing or investigatory situation around automation, the consultant, techie, or account manager will explain the terms. But many of you will want to understand what each acronym means and, more importantly, what each part does before starting out to ensure you know enough to challenge when looking at potential solutions to your problem, and of course, for your own sanity.

As our industry has quite a few acronyms and terms, it may seem a challenge to understand the main ones used in a short period of time. But, here’s some good news. Within the next 20 minutes, you’ll be able to grasp the basic ones. So, when somebody drops CV, DL, or CNN into a conversation — you won’t be confused in thinking they’re talking about a personal profile, slang term, or a news channel, but instead, will be able to put into the context of the automation product you are looking at.

COMPUTER VISION (CV) – EMULATION OF HUMAN VISION

The human eye and visual cortex is an amazing evolutionary system. It gives us the ability to see patterns, shapes, recognize faces and much, much more. Computer vision at its most advanced aims to emulate, or exceed this ability. In order to achieve this, computer vision uses a range of algorithms and machine learning principles to recognize, interpret and understand images.

For computer vision to be effective in daily use it needs to be trained. The training usually takes a form of being fed labelled imagery, example ‘this is a person’ and ‘this is car’, with the more data and variation provided, the more chance computer vision AI has a reference point for future decisions.

In Intelligent Automation, computer vision has a range of use cases from the complex to the simple. In simple use cases, it is used to work with systems to recognize where a button is on a screen and where it needs to click, and in complex use cases, it can be used to recognize when a car is committing a parking violation.

Ultimately, computer vision opens up a whole new set of possibilities for interactions. Providing digital workers with the ability to not only see, but if trained broadly, the ability to recognize the intent of a UI design if a search button is replaced by a magnifying glass, or in a more complex situation mimics the real-life patterns that people usually carry out

DEEP LEARNING (DL)

Deep learning is a subset of machine learning inspired by the structure of the human brain. It differs from machine learning because it learns without the need for human intervention in the process. Where machine learning requires parameters based on descriptions of the input, deep learning uses data on what the object or piece of data is, and how it differs from something else.

For instance, if you got everyone to draw a letter, each person would draw the letter differently. As a human, you can identify the letter regardless of whether a child, or an adult drew it — a machine usually would not understand this.

Deep learning gives the ability for this to be understood, by taking an input of the pattern comparing it with data of what something should look like and based on weights and possibilities within the system — giving an output of what the likely letter is.

Taking an unstructured data set and giving it a likely meaning for a decision based on a probability. An application of this is for email triage, or chatbots in simple applications, or more complex applications in medical condition recognition.

CONVOLUTIONAL NEURAL NETWORKS (CNN)

Convolutional Neural Networks are generally used as an effective means of recognition within videos or images. They use weightings and biases to work out what something is based on taught parameters from data. Think of those squares around objects that recognize a car, a cat, or a dog in recent uses of AI shown on tech programs.

Usually, these images have a probability number written next to them, this is taking the data from within the neurons and feeding out an outcome of it being that. So, a square around a cat, for instance, may have a number of 0.976, meaning out of 1, it is that sure that the thing is a cat.

So, given that’s the usual application, what is the basic principle for how they work?

CNN are a type of fully connected forward neural network. Sounds complex, but essentially what it means is, within this network, all the neurons always move forward and they are all connected. The network takes instruction data which is then used to decide what something is based upon spatial relationships of pixels on a page.

In application, this may mean that it learns a nose and mouth are usually a set distance apart, which is then combined with other information about a person’s face to give a decision whether it is a person with a probability out of 1. By analysing an image bit by bit in this way, CNN can decipher to a degree of likelihood how many people are in an image then feed that information as an output matrix for a decision, or another use.

MACHINE LEARNING (ML)

Until the last decade, machines learnt only by following instructions from a person. This works, but it means that machines were always an extension of people, instead of being autonomous. People recognized this and they also knew that people learnt from experience and didn’t simply follow instructions.

With that in mind, they thought what if machines were actually taught by people, so rather than just following instructions, they can learn to understand and reason with a decision in a similar way a human would.

This idea came to fruition in the concept of machine learning with three key approach types; supervised, unsupervised and reinforcement learning. All with the end of goal of helping machines make decisions either autonomously, or semi-autonomously, to help them adapt to changes they are exposed to and deliver the best results in the shortest time frame — without needing to constantly refer back to a person for direct instruction.

NATURAL LANGUAGE PROCESSING (NLP)

The basic meaning of this acronym is easily understood if you separate the phrase into ‘natural language’ and ‘processing’. The ‘natural language’ part, in this context, means the human language, how we communicate via speech or writing, and the ‘processing’ part is how a computer works on this information. So, Natural Language Processing means how computers can process our language. This is what the acronym means, but how does it achieve this complex feat?

A simple way to understand this is to visualize how a child learns to speak. Firstly, they learn the basic words, then the basic grammar rules, and then they begin to slowly build complexity by learning figures of speech, or other alternative ways to communicate.

Computers learn in much the same way, starting out with simple structures, and ending with trying to understand the irony in a sentence. This can either be taught via a person giving the machine understanding or through feeding large amounts of data via algorithms to give a depth of meaning to the machine of human to human communication.

In automation at this moment, NLP is used to underpin capabilities in chatbots and virtual agents in human conversation. All with the end goal in mind of a machine being able to communicate to the same efficacy as a person.

OPTICAL CHARACTER RECOGNITION / INTELLIGENT OPTICAL CHARACTER RECOGNITION (OCR / IOCR)

Despite living in a digital age, many businesses still work with paper documentation. In order to work with these documents effectively, many businesses will scan and turn the paper documentation into a PDF. On the surface it would appear this could resolve the problem, however, the PDF documentation is not actually turned into digital text, instead, it is an image of the document, a jpg, for instance.

The result of this is the need for people to manually read the document and rekey the data. The technology used to overcome this problem is OCR and for more accurate processing iOCR. So, what does it do? And, what can iOCR do that OCR can’t?

Let’s take an example of an invoice. If the invoice has static information such as the invoice number in the top corner and the cost in the bottom right, OCR can be used effectively with few exceptions to read, understand and digitize the information. However, if the information is not static and fluctuates due to variations in invoices, OCR will flag more exceptions and result in a return to people reading the scanned documents.

Thankfully, iOCR can help in this situation. As iOCR can learn from peoples’ actions, or through pattern recognition, if the document doesn’t vary wildly, the success rate can significantly improve. As it continues to learn by recognizing recurring information patterns, it can see if the product name or invoice number has shifted corners. All of which results in fewer exceptions being flagged and gives people back more time, and in the cases of automation, allows digital workers to perform the whole process.

ARTIFICIAL INTELLIGENCE (AI)

Up until the early 1990s, AI was understood as the general intelligence of machines, meaning they are self-aware and have abilities which equal, or exceed human intelligence.

This was reflected in films from the time such as The Terminator in the 80s, or HAL from Kubricks 2001: A space odyssey in the 60s. Today, AI has taken on a wider meaning, often referred to as ‘applied AI’, AI used in current automation systems and in IT systems is generally used to simulate part of human intelligence in a process.

AI deployed in systems provides the ability for machines to learn, reason and self-correct. This results in a machine which can intake information within a rules-based structure, reason on these rules to meet conclusions based on probabilities and self-correct current trajectory if they believe the current action is going to be unsuccessful.

The ability to apply intelligence to parts of machine interactions gives them the ability to recognize speech, recognize faces via computer vision, or overcome process decisions without needing human intervention.

RECURRENT NEURAL NETWORKS (RNN)

Traditional neural networks have limitations. The major one being they don’t maintain the information, so every time they try to think about something they have to do it from scratch. Recurrent Neural Networks address this challenge by forming loops of networks that allow information to stay within the architecture. Sounds simple, so what does this mean in terms of processing and what can be achieved?

Let’s take an example to explain this using a person and a sequence of context. Think about the following — a dachshund is a type of _______. As a person, it is easy for you to fill the gap in the sentence, or sequence, with dog. This is using information in the sentence in relation to your previous knowledge.

Essentially, this is the logic for how recurrent neural networks use the sequential structure of data to work something out — hence the name recurrent. The operation of a neural network exploits the sequential structure of data to loop information from previous experience and the current input to analyse every element of a sequence.

This means that RNN is made specifically for information that works sequentially, think the text, or speech example above, and many others such as time, sensors or videos. All of which are giving computers and automation the potential to achieve more by being able to use multiple information inputs to work out sequenced data outcomes.

ORCHESTRATION

Orchestration isn’t exactly an acronym. It’s here because it’s an important term within automation that is used regularly and often misunderstood, so we thought it was key to put it in. Orchestration is one way out of three main approaches of managing automation, with the other two being manual and scheduling.

Firstly, the glaringly obvious one; manual. Manual is quite simply a person triggering a job, usually for a specific process or task. The next one is scheduling — the most common technique for people managing automation platforms — works by instructing the digital workers to perform a task every 2 minutes between specified times. Although this is the common approach and is more autonomous than manual — it has its drawbacks.

Namely that once the digital worker has completed the task it will sit idly until the next one. This was the accepted outcome, until the arrival of orchestration. Orchestration leverages data and algorithms to gain an understanding of when the best time would be to perform tasks or assign themselves to other tasks instead of sitting on the bench. This approach delivers peak efficiency and means digital workers aren’t slacking off or being ‘part-timers’.

NATURAL LANGUAGE GENERATION (NLG)

Natural language generation is simply taking data that a machine understands and human can’t, and turning it into language that people can understand. We are surrounded by so much data that it becomes overwhelming and can’t be comprehended by the human mind alone. But, machines can comprehend this information and NLG gives the capabilities to feed it back to people in terms we can grasp.

The way NLG is spoken about above is the more complex end of the spectrum when talking about its wide applications today. A use today would be for something around financial advising for instance. The machine scans the market for data and brings together a stock overview.

For example; Your stocks for (company name ‘A’) today have dropped by (x number of points), your other stocks (‘B’) has gone up (x amount).

From your AI analysis of the market and data, we advise you to sell (A) and invest in (B) due to the predicted achievements of (insert predicted data) rise.

While this is simple, it demonstrates the capabilities currently being used and how the future is heading towards NLG, giving us an understanding of data which we couldn’t possibly compute in our own minds.

PROOF OF VALUE (POV)

In order to explain Proof of Value you need to understand Proof of Concept, or POC. POC is a common term which is used across software products with a simple meaning; proving the concept, or technology works as claimed. In the automation industry, this usually means showing that a process can be automated and a simple one at that.

Within automation, a POC stands as a waste of time – attempting to prove a concept that has been proven time and time again from America to Australia. This is where Proof of Value, or POV, comes in. Proof of Value may just sound like something a marketing committee came up with, but it’s so much more than that.

A POV is about showing that the business case for automation can be delivered at scale for all their business needs. While a POC will look at simple things such as ‘does the technology work as expected?’ and ‘how has it been deployed?’ a POV will scope the business case, the transformation and map, measure, design and forecast the potential outcome with leadership sponsorship.

ROBOTIC PROCESS AUTOMATION (RPA)

Robotic Process Automation or RPA is a term for a piece of software, or a ‘robot’, which carries out tasks and activities within systems, or applications, in the same way, a human would. The software is perceived as a ‘robot’ because it works in a robotic way, completing tasks automatically in the same way a human would. This element of the software is a deviation from previous automation products.

Previous automation products would need modification to applications, or systems in order to carry out processes and tasks. Robotic Process Automation works differently. It interacts with systems and applications utilizing the same interfaces a person does to capture and manipulate the required information for the process.

On top of that, they can work with other methods such as scripts, or web services. The result is a ‘robot’ which can complete an extensive number of repetitive tasks in places where once they were only easily completed by people.

CENTRE OF EXCELLENCE (COE)

The term Centre of Excellence is an acronym with slightly different meaning depending on what industry you find yourself in. Generally speaking, a CoE is usually responsible for providing leadership, best practices, research and support for the rest of the business. In automation, it means the above and more.

A Centre of Excellence (CoE) is vital in any automation deployment to deliver scale and instil an ‘automation first’ mindset. What does that mean in real terms? It means creating the go-to place for employees to gain knowledge and resources on how automation can help their department. Rather than merely setting up a team and assuming success, a CoE must be a place to distribute, reuse and enlighten staff to the possibilities of automation.  The technology lead and developers within a CoE will generally have three main areas to focus on. Firstly, they look at building a pipeline of automations — working out which processes are most suitable and have qualifying potential.

Next, they scope those processes into deployment, being responsible for the execution of delivery — from design to deployment. Before being there to pick up any improvements and support that are needed — which is important in identifying problems and for sharing with the rest of the company experiences of deployments. If allowed to entwine and grow amongst an organization, a CoE can provide lasting automation success.

ENTERPRISE RPA

You don’t use a teaspoon to dig foundations. In the same way, you don’t use simple RPA to automate an entire enterprise. It will be inadequate at dealing with the needs of the organization. Enterprise RPA is built to handle the needs of an organization spanning thousands of employees — with key characteristics to deliver automation at scale.

Unlike simple RPA, or desktop automation tools, Enterprise RPA is not a locally installed solution. No more rooms full of PCs, or locally installed versions on your laptop. Instead, it is built into servers either on-premises or in the cloud, instilling it with the ability to scale and giving the ability for overall control. In this environment, controls, availability and security can be implemented to provide the ability for management of more than one robot at a time and easy auditability.

After all organizations need to know what the bots are doing when they turn down the lights at the end of the day. What’s more, Enterprise RPA has the ecosystem and development structure around it so that it can maintain, reuse and develop automations in a simple, repeatable and reliable manner. In this way, the ‘robots’ or in more advanced AI versions, digital workers, can meet every process perfectly.

INTELLIGENT AUTOMATION (IA)

Robotic Process Automation is the mimic of human actions, Artificial Intelligence is the simulation of human intelligence, and Intelligent Automation is the combination of the two.

It takes the ‘doing’ from RPA and combines it with ‘learning’ from ML and ‘thinking’ from AI to allow the expansion of automation capabilities and possibilities.

IA takes technology such as computer vision, NLP and machine learning and applies it to RPA, allowing the automation of processes that don’t have a rules-based structure. Using IA digital workers can now handle unstructured data and provide answers based on subjective probability.

The result of this is the ability to expand the number of processes that can be automated, from the semi-structured such as an invoice being processed, to the unstructured such as email triage for an organization. But, it goes further than that, supercharging the abilities of RPA through orchestration and the ability to think without requesting human instruction.  Meaning Intelligent Automation gives organizations new efficiency and productivity, and ultimately a new digital workforce to rely on.

NATURAL LANGUAGE CLASSIFICATION (NLC)

Words can have different meanings depending on the context. As a human, we learn how these contexts interlink as we grow up and understand how a word can relate to multiple things depending on how it’s placed. Natural Language Classification is a way of teaching a machine to learn a language which is domain-specific, essentially teaching the machine to understand the context in the same way a human would. Meaning they can understand and respond to words depending on their placement, or meaning in that structure.

An example of this is demonstrated by one of the worlds most recognised brands, Apple. If you take the word Apple on its own you would assume you are referring to the fruit. But, if you are in mobile phone network the word has a different meaning. NLC is used to classify this data with labelling, so when the machine reads the word apple it knows it means a phone type to a phone network, or it could be labelled to mean an apple to a supermarket.

Hopefully, this list of acronyms gives you a real insight into the world of AI and automation. The concept always seems complex, but most of them can at least be partly understood in plain English. Of course, the above doesn’t delve into the deep areas of complex mathematics, – I don’t know about you, but we like to keep our thinking on a business level. After all, automation is about a solution to a problem and by democratizing the use of AI, we hope you can apply these definitions in your quest for the right automation solution for you.

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Honeywell Robotics hub to bank on warehouse automation https://industrialautomationreview.com/honeywell-robotics-hub-to-bank-on-warehouse-automation/ https://industrialautomationreview.com/honeywell-robotics-hub-to-bank-on-warehouse-automation/#respond Fri, 08 Nov 2019 10:17:31 +0000 https://industrialautomationreview.com/?p=1739 Honeywell Robotics hub to bank on warehouse automation

Honeywell is focusing investment on warehouse automation and robotics through its newly created center of excellence in Pittsburgh called Honeywell Robotics, the company announced last week. The center will focus on technologies it sees as transformational in the supply chain, including artificial intelligence, machine learning, computer vision, Internet of Things sensor fusion software, robot-level and system-level […]

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Honeywell Robotics hub to bank on warehouse automation

Honeywell is focusing investment on warehouse automation and robotics through its newly created center of excellence in Pittsburgh called Honeywell Robotics, the company announced last week.

The center will focus on technologies it sees as transformational in the supply chain, including artificial intelligence, machine learning, computer vision, Internet of Things sensor fusion software, robot-level and system-level simulation, real-time robotic control, warehouse execution software applications and advanced mechatronics, Joseph Lui, a robotics leader at Honeywell who will head the new center, told Supply Chain Dive in an email.

“The whole robotics industry is waiting for a leader who can deliver not only discrete robotic solutions, but a complete portfolio of fully-operational end-to-end robotic solutions for rapid customization and deployment,” Lui said, adding that Honeywell is well suited to fill this role.

Honeywell frames its center as a way for customers to work with the company on end-to-end robotic solutions for their operations. Lui said the initial focus is on warehousing but that could expand to manufacturing and pharmaceuticals in the future.

“Technologies are being developed to automate specific supply chain process steps, such as unloading, receiving, decanting, stowing, picking, packing, sorting, shipping, moving, loading, and more,” said Lui, who was previously the director of industrial IoT and automation technologies pertaining to robotics for Amazon.

Honeywell Robotics will benefit from working with Honeywell Ventures, which invests in robotics startups and academia, and Carnegie Mellon University’s National Robotics Engineering Center. Carnegie Mellon and Honeywell have been working together on robotics for more than a year.

“In a period of such extreme growth for robotics, it is vital to have the technical platform along with the domain expertise and real-world data to push technology forward to commercial maturity,” Herman Herman, director of the National Robotics Engineering Center at Carnegie Mellon University, said in a statement last year. The original work between the university and Honeywell focused on controlling and operating multiple robotics applications at once.

Warehouse robotics companies have benefited from hundreds of millions of dollars in funding in recent years. Higher levels of e-commerce orders combined with the promise of faster delivery mean packages have to move through fulfillment and distribution centers at a faster pace than ever before. These robotics companies, and Honeywell Robotics, say robotics will provide the efficiency needed to meet the demands of e-commerce.

“As AI, machine learning and computer vision become commonplace, Honeywell Robotics will create innovative, breakthrough technologies to help customers alleviate skilled labor shortages, reduce safety risks and eliminate inefficient tasks,” Lui said in a statement.

The International Federation of Robotics expects the sales of robots to grow 10% from 2019 to 2020, according to a recent forecast by the group.

Honeywell is actively recruiting engineers and applied research scientists but didn’t say how many people would work at the center.

Honeywell is not the only company investing in facilities dedicated to the modernization of the supply chain. Last month, DHL opened its Innovation Center in Chicago, saying it was a place to work with customers on digitizing supply chain operations.

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