Robotics Process Automation.

RPA.

Its something that companies are expected to spend over $2.4 billion on by 2022, up from $689 in 2018 according to Gartner.

But what exactly is it? And where does it fit in when it comes to helping companies with their digital transformation efforts?

These are big questions I was able to ask during a recent LinkedIn Live conversation I had with Francis Carden, Vice President of Digital Automation and Robotics for Pega a leading customer engagement and process automation platform provider.

Below is an edited transcript from a portion of our conversation. Click on the embedded SoundCloud player to hear the full conversation.

Small Business Trends:What exactly is RPA?

Francis Carden: RPA stands for robotic process automation, and about a million things underneath it, dependent upon who you speak to. To me, it primarily started life as automating applications that run typically on Windows machines on desktops, and sometimes you could automate them a hundred percent and move those desktops to a VM, and they all run by themselves in a locked cupboard, right, properly governed and secured, hopefully. And then Attended RPA was basically, you put it on the desktop and it would automate alongside a human, so you could improve the humans performance by 20 to 40 to 50%. But if you get to a hundred percent, you dont need the human, so you would move it to the server room and [inaudible 00:00:39].

But, predominantly, to me, what it started out as, its morphed into some very different things, not necessarily rightly. But RPA was predominantly automating someone elses user interface, the keyboard, the mouse, the screen, because it doesnt change a process, it just automates the as-is process. And then, of course, it got, Throw some AI at it. That suddenly makes it uniquely different. Or, Throw some API integration in it.

But then, to me, those things arent really RPA. If youre automating a UI, youre basically saying, the old processes are fine. No, theyre not, right? You just keeping them alive for longer. Youre adding to debt, right? I think one of the analysts calls it a tax on legacy. Its so true.

And so, for the years Ive told very successful, large implementations of RPA, I never turned around to anybody and said, Oh, its transformation, or Its going to change your life. Its going to change the way you do business. No, its an operational improvement benefit.

Youve got intelligent automation, which is a myriad of technologies, which includes RPA, and RPA typically should be used as a bridge to transform your business. Because any business thats not transforming and just band-aiding stuff together with RPA is not going to be competitive a year or two or three from now, right? Because theyre peers are truly transforming their businesses and dont need RPA or very little of it. And thats got to be ultimately the goal. Nobody really wants screen scraping, right?

Small Business Trends:Talk about intelligent automation.

Francis Carden: I like to take a step back and think about work, right? Work that a human does at the desktop, thats really what were focused on because were not talking about necessarily APIs and the other stuff thats done. We can talk about that later because its of this, but predominantly RPA or the work that gets done by a human, theres a start point. It might be a mortgage loan application. It might be a call because theyre complaining that their network keeps coming down, or their mobile phone keeps breaking, whatever it might be. A call comes in, and then ultimately theres an outcome. And then if all you do is automate the existing way you solve that outcome, all the underlying debt stays around this. Its not a digital process.

Intelligent automation says lets rethink how we want that outcome to occur. We want it to happen faster. We want it to reach out to the customer before they call us. All of those things start to really evolve if you think about it intelligently. Automating a process is not about automating the as is, but automating almost the want to be. Where would you like as a business, that process? If you was to start a new company today, you dont go out and buy 6,000 legacy systems and use RPA to turn yourself into a digital business. You typically build, or you buy some technologies, and you build a digital business. And so you are intelligently automated from the ground up. And RPA is basically trying to not intelligently automate you from the top down.

And so its a matter of using the right technologies, and whats put people off in the past from being able to digitally transform a process, is some things are just hard to do. And so, technically, you might get such a roadblock, you might as well just use RPA. But what we believe is you can automate much of the process using intelligent automation, whether thats low-code or whether thats design thinking to reengineer a process or case management, and then use RPA to plug the gaps that wouldve prevented you getting further along the digital transformation story. And then think about replacing those RPA bots. Weve got customers that build bots only if theres an end of life strategy for them, right? I mean, thats very forward thinking and very creative and very right, right?

Small Business Trends:RPAs, theyre great for, like you said, automating routine kind of mundane tasks. And if the processes that are making up those routine automated, I mean, those routine tasks are bad processes, like you said, it just speeds up the failure and makes the failure more consistent in achieving, as long as you run those processes. But when it comes to actual transformation, thats in intelligence. Thats where, I guess, the umbrella of DPAs come in.

Francis Carden: We both lived in this world for a long time. To automate a process properly, i.e., to rethink it, reimagine it, everybody thinks thats a big ticket item. Its going to take many, many years. BPM [phonetic 00:05:43] was known as its going to take forever, right? Its like ERP. I mean, thats the worst one, but everybody thought that [inaudible 00:05:49]. Ill implement an ERP system in six months, so we digitize the process in three.

But whats changed, DPA, intelligent automation, is that there are new technologies that do not require you to rebuild a process from scratch in years. You can do them in weeks. Weve got customers rebuilding processes properly in days and weeks. And that may or may not include RPA. Often, it does not, but its there if you need it. But if you think about an RPA vendor thats raised all this money, they have to push RPA. Thats their license revenue.

Now, what theyve done is theyve said, Well, lets add some intelligence to RPA. Lets add OCR and some AI around document readings, and lets add some API integration. Its like, Well, thats then not RPA. Thats the stuff weve always had, maybe done better than before. Give everybody that. But I do not believe a digital transformation platform should be built on screen scraping. No enterprise, no CTO Ive ever met says, Yeah, yeah. Were going to go and buy a screen scraping platform [inaudible 00:07:04] an RPA platform to digitally transform my business. It doesnt happen.

And so low-code, to me, is the movement, and underpinning low-code is that citizen developers and IT can collaborate together to look at a process and say, How can we improve this process dramatically? Right? Almost throwing away the existing and just say, Well, imagine that we were allowed to dream, and this is what my perfect process would look like. And then a few buttons later youve actually said, Well, we can start to do that in these days and weeks, instead of these years. And thats what were seeing. Its almost a competition. Its almost now cheaper to build a new process than it is to use RPA to plug the old one because if you take into account the cost of bot maintenance, if you take into account the cost of maintaining those legacy systems and the infrastructure required to do it, and IT and QA and everything else, but if you take a step back and say, well, again, to my point earlier, you lose a new digital business. Dont buy those legacy systems, but you managed to build a digital business, so that they say never the twain shall meet, but that twains meeting now, right?

You are literally seeing companies And we saw it through COVID as well. We saw lots of RPA vendors going out there building some bots, which kudos to everybody who contributed to helping through this pandemic. But we also saw a massive number of companies with Pega building applications from scratch in days, like loan applications in days. Instead of our band-aiding an existing loan application with RPA, we were actually building brand new loan applications where banks could put those online so that people could apply for loan. The loan be processed. And when you talk about building an application in a week or two, people dont believe you, but its true now. Thats DPA or intelligent automation.

Small Business Trends: So do you see companies looking to do digital transformation starting with RPA thinking they are doing intelligent automation?

Francis Carden: So, intelligent automation, you can start with it and use RPA, or you could use RPA and come back to it later. But every one of our clients, whether theyre with successful with RPA or not, needs intelligent automation. And thats the depth and breadth of DPA, or as Gartner calling it hyper-automation. I think HFS called it intelligent process or measure, whatever the acronym, its about doing it right now. And the time is now when weve got to automate these processes correctly. And that is the conundrum. The word automate implies automating something as is. Why does the word automate count to building something new, kind of is an oxymoron. Youre not automating it, right?

And I think of computerization as the automation of the way things were done manually, and RPA is just automating computerization. Its still the way things were built to do, what used to be done manually. Digital transformation or intelligent automation is about automating the way to do it properly. Now you can. You couldnt do it that way 10 years ago. The technology was too hard, right? Big projects. Now you can build things in days and weeks and months that used to take years, and its transforming the game for the entire industry in every sector.

This is part of the One-on-One Interview series with thought leaders. The transcript has been edited for publication. If it's an audio or video interview, click on the embedded player above, or subscribe via iTunes or via Stitcher.

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Francis Carden of Pega: RPA Doesn't Automatically Mean You're Adding Intelligence to Your Automation Efforts - Small Business Trends

In the last 20 years, CPUs and networks improved by a factor of 10,000X. According to Moores Law, in the next 20 years, they will improve by another factor of 10,000X. During the 40-year design lifecycle of todays industrial automation (IA) architectures, computers will be a mind-boggling 100,000,000X more powerful. Its hard to overstate the implications.

Using such power will determine which companies, industries, and even economies win or lose. For todays designers of tomorrows long-lifetime systems, enabling intelligent software is the only significant factor.

In fact, this is already happening. In industry after industry, software is becoming the most valuable part of every system. IA has been an exception to this rule. Nonetheless, like autonomous cars and intelligent medical systems, IA can use sensor fusion, fast distributed reactions, and artificial intelligence (AI) to replace rigid or manual processes with smart autonomy.

Developing architectures seek to solve the problems of the last 20 years, such as reconfiguring workcells, small lot sizes, flexible automation, and vendor interoperability. These will be far more easily solved with flexible software than rigid specifications. The future belongs to software.

The Harsh Truth

Todays discrete automation systems use a simple hardware-focused architecture. A programmable logic controller (PLC) connects devices over a fieldbus. The PLC controls the devices and manages upstream connections to higher-level software such as human-machine interfaces (HMIs) and historians. Factory-floor software reads sensors, executes logic, and drives actuators, thereby implementing a repetitive operation in a workcell. The factory consists of a series of these workcells, each with a few dozen devices.

Workcells arent so much programmed as they are configured. Manufacturing engineers or technicians use a palette of devices to implement a function in the cell. The goal of this design is to make it easy to assemble workcells of devices with little software effort. Unfortunately, the goal of minimizing software in plants precludes using advanced computing and intelligent systems. As eloquently put by one industry leader:

One of the harsh truths about manufacturing software is that it is not developed by software engineers or computer science majors. We would not regularly ask an electrical engineer to design a mechanical system, or a chemical engineer to design an electrical system, but we often ask mechanical, electrical, and chemical engineers to design and develop software systems.Brand, Dennis L. (2012-11-13T22:58:59). Plant IT: Integrating Information Technology into Automated Manufacturing. Momentum Press.

Brandls harsh truth simply cant continue. Superior custom software will take its place above reliability, performance, and interoperability as the key to competition. That means industrial companies will need to write their own code with competitive, professional software teams. You cant win a software war with someone elses software.

How can we enable this future? First, we need to understand the available industrial architectural frameworks. Then, we can put them together to enable software-driven IA.

What are OPC UA and DDS?

The top industrial architectural frameworks are the OPC Unified Architecture (OPC UA, managed by the OPC Foundation), and the Data Distribution Service (DDS, managed by the Object Management Group). Both have widespread adoption in industrial systems, although not in the same use cases (Fig. 1). DDS finds traction in applications in medical systems, transportation, autonomous vehicles, defense, power control, robotics, and oil and gas. OPC UA is also used in many of these industries, but not in the applications. Rather, OPC UA is mostly employed in discrete automation and manufacturing. In practice, theres almost no overlap in use cases.

1. OPC UA integrates software supplied from external sources, like devices with embedded software, HMIs, and historians. It focuses on vendor interoperability by specifying standard interfaces as companion specifications. Theres no facility for custom-written software, so most systems have little to no end-user software. By contrast, DDS provides a common data modelthe key requirement for writing distributed software. It therefore supports teams of programmers building large distributed systems with extensive custom functionality. Unlike OPC UA, there are few sources of supplier software.

DDS supports publish subscribe, as does the new specification for OPC UA PubSub. But OPC UA does notand will neverdo what DDS does. DDS is fundamentally a software-development architecture; OPC UA is not. Thus, the question isnt about choosing DDS or OPC UA. The question is understanding what they do and deciding which one is needed for your design, or if you need both.

That of course leaves the question: Why are they so different?

DDS evolved as a software-development framework for control systems. The first DDS applications were feedback-control systems for intelligent distributed robotics communicating over Ethernet. They used extensive custom software written by computer scientists. Almost all DDS applications integrate an AI component or very smart algorithms. DDS directly targets software teams building intelligent distributed machines.

By contrast, OPC UA grew up in the plant environment where, as Brandl points out, software engineers are rare. Its prime goal was to help PLC-centric workcell designs select different vendor hardware without writing software. The workcells endlessly repeat an operation, but theyre not truly smart. OPC UA seeks to minimize, rather than enable, software development.

We must differentiate integrating existing software components from writing new software. OPC UA supports software integration of modules like HMIs and historians. However, it offers no facility for composing intelligent software modules. Its not a software-development architecture for distributed applications.

What Does OPC UA PubSub Do?

OPC UA PubSub is a simple way to send information from a publisher to many subscribers. A publisher collects a DataSet at regular intervals and writes it to its subscribers. A DataSet is pulled out of the OPC UA information model, essentially a list of key-value pairs. On the other end, the Subscriber unpacks it and pushes it into the UA information model. Theres also support for simple structured data types.

Most users plan to use OPC UA PubSub with the UDP transport. It has some simple options. It can chunk data thats too big to fit into a network packet (usually only about 1.5 kB). It can resend every message a fixed number of times in hopes of better reliability. But it doesnt guarantee reliability by detecting and retransmitting lost messages. And, it rigidly locks execution; every subscriber must get the same data in the same format. OPC UA PubSub also supports other non-real-time messaging middleware options, MQTT and AMQP.

Fundamentally, OPC UA PubSub offers a simple mechanism to connect variables on a set of tightly coupled devices. Every device gets the same data at the same rates at the same time. With the right companion specifications, it can ensure device interoperability. UA PubSub is very new; there are few deployed applications.

What Does DDS Do?

Unlike OPC UA, DDS supports modular software-defined systems with a simple concept: a shared global data space. This simply means that all data appears as if it lives right inside every device and algorithm in local memory. It is, of course, an illusion; all data cant be everywhere. DDS works by keeping track of which application needs what data, knowing when it needs that data, and then delivering it. So, the data actually required by any application is present in local memory on time. Applications talk only to the local data space, not to each other.

This is the essence of data centricity: Instant local access to all data by every device and every algorithm, at every level, in the same way, at any time. Its best to think of it as a distributed shared memory, similar to a distributed control system (DCS) sandbox RAM, implemented virtually.

Each DDS module specifies the schema (types) it can exchange in memory. DDS controls the flow into and out from this structured memory with QoS parameters that specify rate of flow of data, latencies, and reliability. There are no servers or objects or special locations. Since DDS applications interact only with the shared distributed memory, theyre independent of how other applications are written, where they live, or when they execute. Its a simple, naturally parallel software architecture across the entire system.

DDS implements a long list of features to support software-driven distributed control, including:

Some Key Differences

OPC UA PubSub provides none of the data-centric features that are the core of DDS. Lets look deeper.

Interoperability

OPC UA enables device interoperability through device models and companion specs for hundreds of situations. OPC UA devices crowd tradeshows, pinned to the wall as evidence of interoperability. The consistent message: Factory engineers and technicians can combine devices into workcells with OPC UA without writing code.

In contrast, no devices today come with DDS pre-installed. Thats because DDS doesnt integrate devices per se. Instead, DDS integrates software modules. To add devices to a system, DDS users model devices as software.

Instead of specifications for every permutation, DDS integrates everything through a system data model. It maps device functions from a vendors native API to the system data model. DDS vendors offer very sophisticated bridging and data routing technologies. Thus, the popular layered databus architecture allows systems to grow by connecting data models between layers (Fig. 2). This also means that a DDS system can connect to devices despite different interfaces, to web technologies, and even to OPC UA.

2. Autonomous vehicles are revolutionizing the automotive industry. With a data-centric approach, DDS handles both on-vehicle and control-room use cases. Data routing provides a consistent data model throughout the system, thus building a reliable, large-scale infrastructure. To adopt software drive, the IA industry needs a similar system approach.

Coupling

Coupling is a measure of interdependencies between software and system components. Coupling can be obvious, like coupling clients to servers. It can also be subtle, such as when software modules must start in a particular order or execute at the same rate.

The DDS data-centric design makes it seem like all data is local, so the application isnt coupled to any other application. DDS controls interactions with the data through 21 different QoS policies, including deadlines, latency budgets, update frequencies, history, liveliness detection, reliability, durability, ownership, ordering, and filtering. It also converts types that evolve, as long as they are still close enough to be compatible.

DDS runs on hundreds of platforms and over dozens of networks transparently. Theres no dependence on language, operating system, chip architecture, or type of network used. Thus, data-centric applications work in parallel and share data transparently without interference. Coupling is only by design.

By contrast, OPC UA applications talk directly to each other. For instance, in PubSub, every subscriber gets exactly the same data from the publisher at the same rate. Each subscriber gets all of the dataflow, so the whole system also relies on having similar connecting network properties and processor speeds/loads everywhere. All subscribers must have the same understanding of the data being sent; therefore, versions must exactly match. Each added participant adds a dependency, directly coupling the system.

Fundamentally, decoupling helps applications and devices work independently. With a few subscribers in a workcell, coupling may not matter. Coupling can be good, for instance, for synchronous feedback control with minimal delay. In larger systems, coupling is bad; loosely coupled systems are easier to scale, test, build with distributed teams, deploy, understand, and maintain. Each source of coupling is a real problem, and combining many sources is debilitating. Good software architecture should avoid coupling unless absolutely required to affect the application.

Discovery

DDS automatically discovers named topics across the system regardless of where the application lives. Applications dont have to do anything or have any knowledge to find the data they need.

OPC UA doesnt support discovery in this sense. Subscribers query a server to get a configuration that includes the publisher of the data they require. They can also introspect a publisher to see what it can publish. Both are active queries; OPC UA doesnt perform system-wide automatic discovery.

Security

OPC UA and DDS use fundamentally different approaches to security. OPC UA secures the underlying transports. The various pubsub middleware options and client-server require different security implementations (and often, certificates). Its possible to set up connections between OPC UA clients and services securely, but theres no generic way to indicate which data is allowed to flow to which client.

DDS also can secure the underlying transports, but the primary approach instead provides overall dataflow security regardless of transport. DDS is fundamentally a flow-control technology. So, with a signed permissions document that describes allowed read and write access, DDS can secure and control the dataflow itself (Fig. 3). This requires no code; security can be added after the entire system is running.

3. Most security schemes secure the system edge, host, or network. These are important, but they dont match the application. DDS security adds the ability to control the dataflow itself, creating a system-wide layer that depends on the application rather than implementation like network, operating system, or device location. It also allows for directional security (e.g., read but not write).

Scaling

DDS supports domains that separate systems, partitions within a system, and transparent routing between subsystems and networks. With transparent routing, the data sources can be very far away. DDS systems can grow to hundreds of thousands of applications. Top to bottom, across subnets, or with any pattern (pubsub, request-reply, or queuing), DDS offers a unified data model, a single security model, and consistent access to data.

Since there are few deployments, scalability for OPC UA PubSub has yet to be demonstrated. However, OPC UA PubSub over UDP isnt designed for more than a few devices on a single network. With MQTT or AMQP, a publisher can talk to a cloud server, but not to other OPC UA PubSub subscribers. OPC UA client-server is designed to roll up workcells into a larger factory. So, OPC UA doesnt offer unified system data access in the same way as that of DDS.

Filtering

OPC UA subscribers can select a DataSet with a filter, but only to ensure reception of the correct data. They can also limit access to a single publisher.

DDS has extensive filtering. QoS matching enables subscribers to receive information only from capable sources. The time-based filter decouples the speed of producers from that of the users of information. Content filtering analyzes the content and delivers only data that fits the specification. Together, these filters ensure delivery of the right data to the right place at the right time with minimal wasted bandwidth.

Use of TSN

TSN, or Time Synchronous Networking (IEEE 802.1), is a developing set of standards that build on the existing Ethernet design to deliver data in bounded time, aka isochronous networking.

With TSN, OPC UA PubSub can deliver better real-time performance. TSN can be reliable, so the lack of reliability in OPC UA over UDP isnt as critical. However, since TSN is a flavor of Ethernet and requires central configuration, its limited to smaller, single-subnet systems.

DDS was initially developed for real-time control over a network. QoS settings can optimize use of the underlying network, supporting everything from slow, lossy networks like satellite links to isochronous transports like backplane buses and switched fabrics. On capable hardware, it offers predictable and fault-tolerant one-to-many delivery with bounded latencies.

Combining DDS with TSN allows more distributed determinism. A DDS over TSN system can combine high-level data access with true real-time performance. The OMG has an active standard in progress for DDS over TSN scheduled for release in Q4 2020.

When Should We Combine Capabilities?

OPC UAs main use case is to help manufacturing engineers build workcells without writing software. Its used in manufacturing things, but not as software inside the things being manufactured. In stark contrast, DDS users are software engineers building applications that go into things; DDS is only used to operate things. Thus, UA is about making things. DDS is about making things work.

Theres overlap coming in terms of things that make things, aka smart manufacturing systems. These will soon need sophisticated system software and custom programming.

The OMG recently passed a standard for an OPC UA/DDS gateway (Fig. 4). At its most basic level, this gateway takes the OPC UA information model and makes it available within the DDS global data space. The primary use case is to convert OPC UA-enabled devices to DDS devices. OPC UA devices can simply join the DDS network.

4. The DDS-OPCUA gateway standard connects an OPC UA system to the DDS global data space (A). Conceptually, it makes the OPC UA system data seem available to DDS software applications. The primary use case for the gateway is to enable devices that support OPC UA to participate in a DDS domain (B). Note that this allows intelligent software applications to access any OPC UA device. Together, these standards can provide attractive software development and easily integrated devices (C). It lets AI work at every system level.

In a large intelligent system, the DDS-based software environment can thus coordinate and work with the OPC UA devices. This allows for both sophisticated software and interoperable devices.

Note that this design offers many opportunities to leverage AI and intelligent software. At high levels, DDS interfaces to cloud-based intelligence. Future generations of this design can also implement AIs or smart algorithms for device interoperability

The Smart Machine Future

Historians will look back on our time and wonder how we got by without smart machines. The transition will not be smoothproduct lines, companies, and entire national economies are at stake. Brandls harsh truth may be the most dangerous paragraph in automation. That truth will not survive the smart machine era.

So, software excellence must join the manufacturing technology mix. In the next 20 years, manufacturing system performance will not improve by a factor of 10,000. Interoperability will not become 10,000X more valuable. But software will become 10,000X more important. Thats the inevitable result of exponential computing growth. Any architecture that doesn't target using compute power as its primary goal is already obsolete.

Does industrial automation need to adopt software development? Will future manufacturing systems compete primarily on unique user code? The software future says yes.

Stan Schneider, PhD., is CEO of Real-Time Innovations.

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Software Will Determine the Future of Industrial Automation - Electronic Design

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Measuring Automation Light Grids Market Report, History and Forecast 2015-2025, Breakdown Data by Manufacturers, Key Regions, Types and Application -...

Over the years, Parrot and Dronisos have worked on various projects together, and today they announced they will be exploring drone automation with Parrots ANAFI drone platform. The two have previously created record-breaking light shows and drone dances.

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In the past, Parrot and Dronisos worked together to bring the dancing drone show during CES 2016 in its booth. This new way of controlling multiple drones showed the world a new level of automation and fine control over many drones at once. You can watch that here.

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Below is a video of the two companies working together to send up 200 Parrot Bebop 2 drones into the night sky equipped with LED bulbs to create a drone light show during the coronavirus pandemic.

Photo: Parrot

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Parrot and Dronisos join forces to explore drone automation - DroneDJ

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This report focuses on the top manufacturers COVID19 Outbreak IT Robotic Automation capacity, production, value, price and market share of COVID19 Outbreak IT Robotic Automation in the global market. The following manufacturers are covered in this report:

COVID19 Outbreak IT Robotic Automation Breakdown Data by Type

Major Application are follows: Banking, Utilities, Healthcare.

Geographically, this report is segmented into several key regions, with sales, revenue, market share, and growth rate of COVID19 Outbreak IT Robotic Automation in these regions, from 2015 to 2025, covering North America (Covered in Chapter 7 and 14), United States, Canada, Mexico, Europe (Covered in Chapter 8 and 14), Germany, UK, France, Italy, Spain, Russia

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Key Questions Answered by the Report

What impact does COVID-19 have made on COVID19 Outbreak IT Robotic Automation Market Growth & Sizing?

Which are the top players of the COVID19 Outbreak IT Robotic Automation market? What are their individual shares?

How will the COVID19 Outbreak IT Robotic Automation market perform in the coming years? What is its current status?

What are the key factors driving the COVID19 Outbreak IT Robotic Automation market?

What opportunities will the COVID19 Outbreak IT Robotic Automation market provide in the future?

Which product/application will secure the lions share of the COVID19 Outbreak IT Robotic Automation market?

What is the structure of the COVID19 Outbreak IT Robotic Automation market?

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Research Methodology of global COVID19 Outbreak IT Robotic Automation Market:

Data triangulation and market breakdown

Research assumptions

Market size estimation using bottom-up and top-down approaches

Research data including primary and secondary data

Primary data includes a breakdown of primaries and key industry insights

Secondary data includes key data from secondary sources

We can customize the report as per your requirements. Our analysts are experts in COVID19 Outbreak IT Robotic Automation market research and analysis and have a healthy experience in report customization after having served tons of clients to date. The main objective of preparing the research study is to inform you about future market challenges and opportunities. The report is one of the best resources you could use to secure a strong position in the global COVID19 Outbreak IT Robotic Automation market.

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Stay Tuned with the Epic Battle in the COVID19 Outbreak IT Robotic Automation Market - Levee Report

New York, Aug. 07, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Industrial Automation Control Market 2020-2024" - https://www.reportlinker.com/p01079083/?utm_source=GNW Our reports on industrial automation control market provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors. The report offers an up-to-date analysis regarding the current global market scenario, latest trends and drivers, and the overall market environment. The market is driven by the need for simplification of complex manufacturing activities, increasing focus on smart factories and changing market dynamics. The industrial automation control market analysis includes product segment and geographical landscape.

The industrial automation control market is segmented as below: By Product Sensors DCS Drives SCADA PLC By Geographic Landscapes APAC North America Europe South America MEA

This study identifies the virtualization of automation control systems as one of the prime reasons driving the industrial automation control market growth during the next few years. Also, value chain integration by automation solution providers and increasing need for open platform architecture for automation software will lead to sizable demand in the market. The analyst presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources by an analysis of key parameters. Our industrial automation control market covers the following areas: Industrial automation control market sizing Industrial automation control market forecast Industrial automation control market industry analysis

Read the full report: https://www.reportlinker.com/p01079083/?utm_source=GNW

About ReportlinkerReportLinker is an award-winning market research solution. Reportlinker finds and organizes the latest industry data so you get all the market research you need - instantly, in one place.

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The Global Industrial Automation Control Market is expected to grow by $ 25.18 bn during 2020-2024 progressing at a CAGR of 5% during the forecast...

LONDON--(BUSINESS WIRE)--Technavio has been monitoring the industrial automation market in life sciences industry and it is poised to grow by USD 1.92 billion during 2020-2024, progressing at a CAGR of over 6% during the forecast period. The report offers an up-to-date analysis regarding the current market scenario, latest trends and drivers, and the overall market environment.

Technavio suggests three forecast scenarios (optimistic, probable, and pessimistic) considering the impact of COVID-19. Please request Free Sample Report on Covid-19 Impact

Frequently Asked Questions-

The market is fragmented, and the degree of fragmentation will accelerate during the forecast period. ABB Ltd., Emerson Electric Co., Honeywell International Inc., Mitsubishi Electric Corp., OMRON Corp., Parker-Hannifin Corp., Rockwell Automation Inc., Schneider Electric SE, Siemens AG, and Yokogawa Electric Corp. are some of the major market participants. The demand for healthcare services will offer immense growth opportunities. To make the most of the opportunities, market vendors should focus more on the growth prospects in fast-growing segments, while maintaining their position in the slow-growing segments.

Industrial Automation Market in Life Sciences Industry 2020-2024: Segmentation

Industrial Automation Market in Life Sciences Industry is segmented as below:

To learn more about the global trends impacting the future of market research, download a free sample: https://www.technavio.com/talk-to-us?report=IRTNTR40901

Industrial Automation Market in Life Sciences Industry 2020-2024: Scope

Technavio presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources. Our industrial automation market in life sciences industry report covers the following areas:

This study identifies open process automation as one of the prime reasons driving the industrial automation market in life sciences industry growth during the next few years.

Industrial Automation Market in Life Sciences Industry 2020-2024: Vendor Analysis

We provide a detailed analysis of vendors operating in the industrial automation market in life sciences industry, including some of the vendors such as ABB Ltd., Emerson Electric Co., Honeywell International Inc., Mitsubishi Electric Corp., OMRON Corp., Parker-Hannifin Corp., Rockwell Automation Inc., Schneider Electric SE, Siemens AG, and Yokogawa Electric Corp. Backed with competitive intelligence and benchmarking, our research reports on the industrial automation market in life sciences industry are designed to provide entry support, customer profile and M&As as well as go-to-market strategy support.

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Industrial Automation Market in Life Sciences Industry 2020-2024: Key Highlights

Table of Contents:

Executive Summary

Market Landscape

Market Sizing

Five Forces Analysis

Market Segmentation by Product

Customer landscape

Geographic Landscape

Drivers, Challenges, and Trends

Vendor Landscape

Vendor Analysis

Appendix

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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COVID-19 Impacts: Industrial Automation Market in Life Sciences Industry will Accelerate at a CAGR of Over 6% through 2020-2024 | Demand for...

New Jersey, United States,- Market Research Intellect has added the latest research on the Food Automation Consumption Market which offers a concise outline of the market valuation, industry size, SWOT analysis, revenue approximation, and the regional outlook of this business vertical. The report precisely features the key opportunities and challenges faced by contenders of this industry and presents the existing competitive setting and corporate strategies enforced by the Food Automation Consumption market players.

The Food Automation Consumption market report is an amalgamation of the key trends influencing the industry growth with respect to the competitive scenario and regions where the business has been successful. Furthermore, the study discusses the various restraints of the industry and uncovers the opportunities that will set the growth course. In addition, a holistic examination of the industry changes caused by the COVID-19 pandemic are also tagged in the report to aid investors and other participants in making well-informed decisions.

Key highlights from COVID-19 impact analysis:

Unveiling a brief about the Food Automation Consumption market competitive scope:

The report includes pivotal details about the manufactured products, and in-depth company profile, remuneration, and other production patterns.

The research study encompasses information pertaining to the market share that every company holds, in tandem with the price pattern graph and the gross margins.

Food Automation Consumption Market, By Type

Food Automation Consumption Market, By Application

Other important inclusions in the Food Automation Consumption market report:

A brief overview of the regional landscape:

Reasons To Buy:

About Us:

Market Research Intellect provides syndicated and customized research reports to clients from various industries and organizations with the aim of delivering functional expertise. We provide reports for all industries including Energy, Technology, Manufacturing and Construction, Chemicals and Materials, Food and Beverage, and more. These reports deliver an in-depth study of the market with industry analysis, the market value for regions and countries, and trends that are pertinent to the industry.

Contact Us:

Mr. Steven Fernandes

Market Research Intellect

New Jersey ( USA )

Tel: +1-650-781-4080

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Food Automation Consumption Market Size, Global Future Trend, Segmentation, Business Growth, Top Key Players, Opportunities and Forecast to 2027 -...

August 6, 2020

By Jeffrey Burt

Channel partners of cloud-based distributor Pax8 are getting access to Liongards Road platform, which enables MSPs to gain better visibility into their end customers systems whether theyre deployed on premises or in the cloud.

The Lowdown: The two companies this week announced a partnership that will give MSPs access to configuration data both historical and up-to-date of a customers entire IT stack to speed up processes and find a resolution.

The Details: The technology from Liongard, a 5-year-old company based in Houston, Texas, enables MSPs to automatically document, audit, and secure customer systems.

Benefits include:

> APIs into more than 30 vendors to ensure documentation is up-to-date.> Capturing historical data to help with troubleshooting.> A custom alerting system that lets MSPs be proactive in dealing with issues.> Data exportability features for reporting.> Integration with Microsoft 365, Azure AD, and Azure public cloud, and with AutoTask, Datto, ConnectWise, Kaseya, BitDefender, StorageCraft, Veeam, and Webroot.

The Impact: The capabilities in Liongards platform help build trust between MSPs and their clients, reduce user errors, and enable IT service providers to more efficiently manage systems at scale.

Background: The partnership with Pax8 comes less than three months after the company raised $17 million in Series B funding, bringing up the total amount raised by Liongard to almost $23 million since its founding in 2015 by CEO Joe Alapat and COO Vincent Tran. The company serves both MSPs and IT companies in more than 20 countries and has seen the number of customers triple over the past 18 months and the number of companies supporting the platform double in that time.

The Buzz: To keep pace with ever-changing IT requirements, we are excited to offer Liongard to MSPs, said Ryan Walsh, chief channel officer at Pax8. Liongards strong, trusted platform enables MSPs to have greater visibility into how their systems are managed. With its capabilities, the solution gives our partners a competitive edge.

Liongard and Pax8 share a similar goal of propelling our partners forward through innovative, intuitive technology that enables greater efficiency and profitability, said Mark Sokol, vice president of marketing at Liongard. Were thrilled with this partnership and what it means for MSPs.

Related Links: CHANNELNOMICS:>Pax8 Hooks Up With RingCentral for UCaaS>Pax8 Bolsters E-Mail Security Services for MSPs>Pax8 Brings CloudJumper, Microsoft Solution to MSPs

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Pax8 Gives MSPs Access to Liongard Automation Platform - Channelnomics