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Ford Takes the Long View with Large-Scale 3D Printing

One of the big practical challenges of printing larger 3-D printed parts is spatial. To get the dimensions precise, it’s best to perform the process in a temperature controlled chamber or oven. Conventional 3-D printing is done vertically, so there is not a practical way to print very tall parts within that chamber/oven without having an extremely tall printer.

engineers at Ford have been testing a 3D printer that builds objects horizontally using a printer called the Infinite Build, developed by the Israeli additive manufacturing company Stratasys. For prototypes, it can produce objects that fit within the print volume of 30”x 48”x infinite. Boeing is also testing the technology.

(Ford Motor Company)

The industrial-sized printer sets the usual configuration on its side and builds out instead of up. The material is also different than conventional 3D printing: Instead of a continuous filament, the printer uses thermoplastic micropellets, and the refilling process is automated to allow for continuous operation for days.

The technology lends itself well to fixtures and tooling applications in the near term. But don’t look for mass production of parts on Infinite Build anytime soon. It still can’t compete with those mass production processes like injection molding.

Ford’s strategy is to partner with 3D printing innovators early in the technology’s development to modify it specifically for their automotive needs.

>> Read more by Laura Putre, IndustryWeek, March 9, 2017

3D Machine Vision Market Poised to Jump 11.07 Percent by 2022

Powered by the increasing use of robotics in the automotive industry, among others, the 3D machine vision market is on target for an 11.07 percent compound annual growth rate between now and 2022, according to market research firm Markets and Markets. Analysts expect the market to be valued at $2.13 billion over the next five years.

Cameras will hold the largest share of the 3D machine vision market for hardware in the next five years. Cameras play one of the most critical roles in machine vision systems, capturing 3D images.

The Asian-Pacific region held the largest share of the 3D machine vision market in 2016, and the region is expected to continue to dominate the industry between 2017 and 2022.

>> Read more by Sheri Kasprzak, Product Design & Development, 3/20/2017

Put Engineering Collaboration Front and Center

For the next step in their engineering technology, Airbus is implementing collaborative engineering, which it defines as “the integration of functional and industrial design teams to produce a single deliverable, an industrial digital mockup (iDMU).”

Researchers at Madrid Polytechnic University found five elements that defined each transitional stage as Airbus moved from traditional to concurrent to collaborative methods. Thanks to consumer-class social media and the use of concurrent engineering practices in software development, the pressure is on product design and manufacturing companies to adopt collaborative engineering procedures.

(Source: digitaleng.com)_

It may not be prudent to use Dropbox, Facebook messenger, or Skype as a communications channel in product design. But advances are being made around the themes of improving workflows, improving access to data and protecting engineering from time-wasting practices or technologies.

Aras Innovator PLM software includes Visual Collaboration, a browser-based environment for model and document review. (Source: Aras Software)

Conversations taking place in product design are not always taking place within the frame of product lifecycle management (PLM). Aras, which develops the Aras Innovator PLM system, identifies three problem areas for engineering collaboration:

1. Security: Email and other forms of direct communications are “potentially insecure … it is important to keep these communications secure, even within the organization.”

2. Context: If an engineer has a question about materials, she might call up a model, but is it the right model? “Context is important in collaboration; engineers must be able to get answers from the right place at the right time.” Too often such searches become “micro-level interactions using email or Dropbox,” McDonald says, further weakening the security as well as potentially leading the engineer in the wrong direction.

3. Verification: There is no consistent, automated way to store, access and verify communications outside the PLM system. This makes it impossible to establish an audit trail, crucial in some industries.

Data in collaborative environments needs to be granular; accessible at its most fundamental level. At the same time, not everyone in the value chain needs the same level of data granularity. Dassault Systèmes’ Ramesh Haldora, VP of Strategic Consulting for the 3DEXPERIENCE platform, says granularity of data is an important reason to move from electronic engineering documents to a single digital platform. Dassault’s digital platform is built based on its core applications: CATIA, SIMULIA, ENOVIA. In this environment, each person in the value chain can access the data they need at the level of detail required, and it the data is always current.

Not every engineering software company is working to provide real-time collaboration as the norm. Siemens PLM distinguishes between synchronous and asynchronous collaboration. Most people prefer asynchronous work; it is working on their own timeline. Engineers need asynchronous collaboration at the bottom of the pyramid and synchronous at the top. It’s not as important.

ESTECO approaches its role in engineering as providing for a team approach. No single expert can do the entire simulation; this pushes engineers to work together. ESTECO sees democratization of engineering data as a crucial piece of creating a collaborative environment.

ESTECO Volta is a new web-based simulation collaboration application, designed to encourage collaborative engineering and knowledge management for the dispersed enterprise. (Source: ESTECO)

>> Read more by Randall, Digital Engineering, March 1, 2017

 

The IoT Impact on Business Models: What Should Manufacturers Do First?

The Industrial Internet of things is going to change business models, and manufacturers that don’t change with the times will see their competitiveness dwindle.That’s what everyone says, particularly automation suppliers. While it may be true, making major investments in these new technologies, without rethinking your entire manufacturing processes, could lead to rash, costly purchasing decisions that negatively impact your business.

IoT concepts have already impacting services in other industries: Uber, Zipcar, and Airbnb challenge the traditional business models.  The fundamental concept behind all three of these businesses is the effortless connection of the user, directly with suppliers, at a lower transaction cost.

In manufacturing, the application of IoT is primarily used to achieve efficient, make-to-order manufacturing, linking the buyer directly with the manufacturing process and all related stakeholders.   These new technologies are providing the building blocks for dramatic changes in the manufacturing industry:

  • 3D Printing/ Additive Manufacturing
  • Product Lifecycle Management (PLM) Software
  • Collaborative Robots
  • Pervasive Communications

Before making major investments in any of these new technologies, manufacturers may do well to rethink their entire manufacturing processes to see how these new possibilities could help. These technologies will continue to evolve current manufacturing processes, directly linking the producer with customers and suppliers, driving responsiveness and efficiency.

Industry 4.0, Industrial Internet of Things, and Smart Manufacturing are still in the early stages of development, and the effectiveness of new approaches is not yet clear. Small, incremental investments in pilot programs might be the best way to help learn in a constructive, productive environment, and could save a lot of time and agony, when major investments are made down the road.

>> Read more by Bill Lydon, Automation.com, March 20, 2017

Smart Motion Control is Awake and Aware

Self-aware devices can acquire and process data, such as diagnostics, and then act based on that data.

Rockwell Automation has designed motion control systems that include multiple self-aware devices working together to create a system-aware asset. This system can be a production line that autonomously reroutes products to a different packaging line after a smart palletizer communicates that it is down. It can also help the line reduce its speed and schedule a maintenance work order after it detects the bearings of a conveyor are overheating.

A self-ware motion control system uses software to analyze sensor data in order to optimize performance. The system is a collection of devices that are aware of the system. They hear the heartbeat of the system. By default, the system is self-aware. It gives itself feedback on position and speed.

Rockwell motion analyzer (Source: designnews.com)

The self-aware motion control system also has the capability to monitor the health of its components. Sensors help users make decisions. Both maintenance and the design engineer can do better with this information.

A self-aware system has the ability to compensate for imbalances and adjust accordingly, without human intervention. An implanted load observer operates in real time as the machine is running. It provides signals for low torque and it helps the machine to maintain stability. It goes beyond traditional auto-tuning to become self-ware in real time.

Like a lot of the new smart manufacturing tools, the intelligence is embedded in the equipment and the system. Even while the system is growing in sophistication, it is becoming easier to deploy.

>> Read more by Rob Spiegel, Design News, March 16, 2017

 

How to Create an Effective Robotics Training Program

Collaborative robots have made it very easy to add automation to your business. They are simple to program so should we train in-house? Training your team allows them to maximize their use of collaborative robots and implement more innovative applications. BUT, how can you ensure that training will be an effective investment, not an expensive mistake?

When it comes to collaborative robotics, there are huge benefits to providing training systematically from the top down. It gives workers a feeling of ownership of the robot. It makes sure everyone is “on the same page” which leads to better innovation in products and robot applications.

Alex Owen-Hill from Robotiq outlines how to build a training program which truly benefits your business.

  1. Assess the big picture goals of your business.
  2. Align these goals with the benefits of in-house robotics expertise.
  3. Quantify your existing resources.
  4. Assess which resources are most valuable for your move to in-house expertise.
  5. Get your stakeholders on board, both the technical team and other affected groups of employees.
  6. Identify key applications for robotics.
  7. Use these key applications to determine which new skills are necessary.
  8. Finally, you are ready to look at types of training and implement a training plan.

Here are some of the popular methods for robot training:

Less Costly More Costly
On-the-job coaching and mentoring One-to-one tutoring
Job shadowing Seminars
Self-directed study College courses
Video presentations External group workshops
E-learning In-house consultant training

A good training program will use a mix of the different types.

You will probably use an external supplier for your initial robot training. However, as the level of in-house expertise increases in your business, members of the team can take over some of the training burden. This is why it is so important to involve your stakeholders from early on, otherwise they may resist what they see as extra work.

>> Read more by Alex Owen-Hill, Robotiq, March 8, 2017

The Perfect Swarm: Drones Descend on Manufacturing

Fitted with super processors and advanced sensors, industrial drones are locked and loaded, ready to bring speed and efficiency to new heights. From light material handling to visual inspection to damage control, unmanned aerial vehicles surpass what humans can do in less time and for less money.

Con Edison in New York have already found that sending a drone to check a boiler pipe is more effective than building 10 stories of scaffolding.  Your company might use them to check building health.

The FAA predicts 4.8 million drone sales in 2017, nearly double 2016’s numbers. Most striking is that sales of commercial drones, which require FAA registration, will increase to 2.5 million. That’s a 416% increase. Drones aren’t toys; they’re legitimate tools that every major supply chain in America is rushing to adopt.

You’ve heard about Google, Walmart, and Amazon’s massive drone delivery projects. Ironically, manufacturing is an area that rarely uses drones, but desperately needs them.  One reason may be the more complicated layout of an assembly plant: people, robots, welding and other processes. Another reason might be the level of skill required to program and/or pilot a manufacturing drone.

Keep in mind, again, it is not a toy we are talking about.  This technology is quite sophisticated, such as Qualcomm Snapdragon Flight platform, which comprises proprietary flight control software, a 12-g mother board the size of a credit card, a 2.26Ghz quad-core cpu, gpu, dsp, a 4K camera, comprehensive wireless connectivity, and it’s loaded with sensors. These include the accelerometers, gyros and cameras that will keep the drone aloft and able to fulfill jobs ranging from photography to visual inspection.

Qualcomm's 3D-printed drone.

Qualcomm’s 3D-printed drone. (Photo credit: Debbie Lefever)

Using the onboard cameras and sensors, the drones are able to autonomously determine their own flight paths, finding the most efficient routes, while avoiding obstacles, maintaining elevation, and countering adverse winds or loss of GPS signals.

There are many sectors that can take advantage of this technology to become more productive and efficient.

>> Read more by John Hitch, New Equipment Digest, March 10, 2017

Jack, MAC and Jill

Assembly line avatars help Ford Motor Co. reduce worker injury and improve vehicle quality.

Anthropomorphic test devices (ATDs), a.k.a ., Crash Test Dummies, have been used by automotive test engineers for many years to make car owners and their precious cargo safer.  But the people who assemble those cars can experience a number of types of injuries, many of which are caused by repetitive motion or overexertion.

Ford Motor company has been working to change that and since 2003 has reduced the injury rate for its “industrial athletes” by more than 70 percent. This has been accomplished through a variety of techniques, including analysis of workers’ movements in the company’s motion capture lab, which is powered by digital cameras and motion tracking software from Motion Analysis Corp. (MAC).

Tracking their motions helps to understand the actions that are required to manipulate a part, how well they can see what they’re doing and whether we need to redesign a component to make assembly easier.  This information is then applied during new vehicle planning.

(Source: fsmdirect.com)

Like in a video game, virtual reality headsets immerse an operator in a futuristic workspace with motion cameras tracking their every move. And 3-D printers are used to construct mockups of vehicle components, simulating a tight corner in an engine compartment or a hard-to-reach bolt on an undercarriage. The collected data is then fed into a series of analysis tools. One of these is Jack, a human simulation tool from software provider Siemens PLM.

Jack provides invaluable information about the mechanics, energy expenditure and mechanical stresses faced by human bodies in industrial settings, including their posture. Combining the Jack human simulation capability with assembly process simulation allows them to optimize how workers perform in the production environment. A simulation begins by selecting the appropriate body size, shape and sex (yes, there is a Jill) for the human that’s being modeled.

One additional benefit comes from the reduced need for tooling and prototypes, spending time and money only to discover a product is difficult to assemble. With Jack and the other simulation tools Ford has at its disposal, that information can immediately be relayed to the engineering department for improvement.

Human model Jill attempts to connect a hose inside an engine compartment. These and similar simulations identify areas for ergonomic improvement.

Human model Jill attempts to connect a hose inside an engine compartment. These and similar simulations identify areas for ergonomic improvement. (Source fsmdirect.com)

>> Read more by Kip Hanson, Fab Shop Direct Magazine, 2017-03-17

 

Internet connected ‘smart’ devices are stupid about security

It’s possible to use your smart phone – and sometimes just your voice – to control everything from your TV to your lights, your thermostat and shades, even your car or medical device. But how safe are your connected devices? Experts say tread carefully, but don’t freak out.

Research firm Gartner expects there to be 8.4 billion connected “things” in use in 2017; by 2020, this number could reach 20.4 billion. For businesses, smart electric meters and commercial security cameras are expected to be the most popular “internet of things” products.

Such gadgets are convenient, but they can present easy targets for hackers. There’s a growing call for regulation to secure connected devices, but it’s unclear whether this will happen. According to Homeland Security, the growing dependency on network-connected technologies is outpacing the means to secure them.

Forrester Research analyst Josh Zelonis suggests that consumers can’t wait for the government to fix things. Instead, he said, people have to demand that manufacturers are accountable for the security of their products and that they support the products throughout the product’s lifetime, not just when it’s sold.

Easier said than done.

Many people don’t realize they have to secure connected devices with passwords like they do with computers. If a device comes with a default password, it needs changing the moment you hook it up. Same with Wi-Fi.

Cheaper devices from no-name companies also pose more of a security risk. Smaller companies don’t have the resources (or willingness) of the large companies, such as Apple, Samsung, and Amazon, to continuously fill holes in security.

In short, don’t buy from smaller vendors; don’t buy devices that don’t encrypt data everywhere; change the password if you can.

>> Read more by Associated Press, Plant, March 9, 2017

Flippy robot takes over the hamburger station in California restaurant

At a Caliburger restaurant in Pasadena, California, Miso Robotics and Cali Group have taken the wraps off Flippy, a “collaborative kitchen assistant” that uses computer vision and deep learning to take over the job of grilling burger patties and leaving the chef to do the less grease-spattery jobs of assembling the sandwiches.

Flippy is a low cost, stand-alone robot designed to be used in restaurant kitchens without the need for special modifications. Using computer vision and an adaptable deep learning system, it’s designed to handle the tedious job of watching and flipping burger patties.

Flippy can identify what is on the grill (including an intruding human hand), judge its degree of doneness, and transfer the burgers to the bun for a human chef to complete assembly. In addition, it can adapt to and avoid bumping into its human co-workers for greater safety.

(Source: New Atlas)

Flippy’s maker, Miso Robotics, says the system continuously learns from its experiences to improve over time, similar to self-driving vehicle technology. Their proprietary AI software allows the kitchen assistants to be adaptable and therefore they can be trained to help with almost any dull, dirty or dangerous task in a commercial kitchen — whether it’s frying chicken, cutting vegetables, or final plating.

>> Read more by David Szondy, New Atlas, March 8, 2017

Factory flyover

Whether it’s to fly over the Eiffel Tower, whiz through the Grand Canyon or see what the top of your house looks like, most of us have at least played with Google Earth. The software application displays 2-D and 3-D imagery of nearly every point on the globe, allowing users to zoom in and pan around, drop pins on interesting places and even contribute to the site’s vast collection of data by submitting their own 3-D buildings or aerial imagery.

The technology, which also powers Google Maps and similar applications, has helped revolutionize the way we look at our planet, giving us the opportunity to virtually visit places we otherwise would never experience.  But it doesn’t show us what’s going on inside buildings.

Thanks to Allison Stephens and the team at Ford’s Advanced Engineering & Technology department, that capability is available for Ford employees, at least. Stephens is responsible for much of the work Ford has done over the past 30 years to improve worker safety and she’s also heavily involved in virtual manufacturing and assembly line simulation. Several years ago, she found herself wondering how her counterparts at other factories were performing certain activities. Stephens decided to do something about it.

Not being able to see how other plants set up certain manufacturing lines, Stephens thought it would be nice to have something like a Google Earth that they could use as a communication platform to see what’s happening at different locations.

Having worked closely with Siemens PLM, Stephens mentioned the idea and the Siemens team looked for ways to introduce Google Earth-like capabilities into the company’s Tecnomatix suite of products.  Tecnomatix is a portfolio of digital manufacturing solutions, including process design, logistics and material flow, work instructions, factory optimization, dimensional quality, issue tracking, and many additional management and optimization functions. One of these solutions is Intosite, a cloud-based application that peels back the top of the factory and allows manufacturers to look inside for a 3-D view of their production floor. Work centers and other points of interest can be tagged, asset capabilities shared and what-if scenarios quickly tested.

Siemens worked with Google and leveraged some of their technology, resulting in a map-based system where they can sit at a desk to “break through” the ceiling at any of Ford assembly plant and fly through, just like you do on Google Earth. They don’t necessarily see live feeds (yet), but they can see all of the workstations and assembly line layouts. Then what they can do is pin information to those workstations – photos, simulations, videos or any other pertinent data that they want to make available to anyone within the company.

The entire production floor at Ford’s Wayne, Mich., assembly plant is easily visualized, giving manufacturing engineers the ability to perform what-if scenarios and providing greater possibilities for optimization.

Of course, the security surrounding Ford’s Intosite implementation is multiple levels deep, and it’s accessible only to those with the proper clearance. Intosite has become an invaluable learning tool for engineers and assemblers alike. It’s also given Ford employees greater opportunities to innovate and experiment, to share product data and collaborate on designs without having to travel across the country.

>> Read more by Kip Hanson, Fab Shop Magazine Direct, 2017-03-17

Stratasys Adds To Materials Family: FDM Carbon Fiber-Filled Nylon and Extra-Flexible, Tear Resistant PolyJet Family

Stratasys recently announced two new advanced materials: FDM Nylon 12CF – a carbon fiber-filled thermoplastic strong enough to replace metal components in a range of applications; and, for the PolyJet process, Agilus30 – a new line of high-durability flexible materials that can withstand repeated flexing without tearing or deforming.

FDM Nylon 12CF: Best Stratasys FDM Stiffness-to-Weight Ratio

The first high-performance composite material to replace a range of metal applications available for Stratasys FDM technology, FDM Nylon 12CF is ideal for rapid prototyping, strong, light-weight tooling and end-use parts.

Containing 35 percent chopped carbon-fiber by weight, FDM Nylon 12CF offers the best stiffness-to-weight ratio among Stratasys FDM thermoplastics, meeting functional performance testing demands in automotive, aerospace, recreational goods, and industrial manufacturing sectors.

FDM Nylon 12CF will be of special interest for the following users and use cases:

  • Manufacturing engineers that produce manufacturing aids, such as jigs and fixtures, where high material stiffness and strength is required and there is great benefit to the significant weight savings over metal tooling components.
  • Design engineers making low-volume production parts with unique structural requirements, where high strength in one-direction is required.
  • Design engineers making low-volume production parts with unique structural requirements, where high strength in one-direction is required.

FDM Nylon 12CF beta customer Utah Trikes is taking advantage of the material’s properties throughout its development and production process to make significant cuts to its product development times.

“The excellent strength and stiffness-to-weight ratio of the FDM Nylon 12CF material is a game changer for us. It means we can prototype almost every part of our product on Stratasys FDM 3D Printers in under two weeks, where in the past it could take us over two months,” said Ashley Guy, president and CEO of Utah Trikes.

“I no longer have to constrain my designs because of prototyping limitations. Now I can focus on designing better, more functional parts without worrying about how to shape the aluminum or how to lay up carbon fiber onto the molds. Stratasys FDM Nylon 12CF parts can be 3D printed faster, with superior stiffness-to-weight performance and with better repeatability than any other 3D printing technology or vendor we’ve seen,” continued Guy.

“We believe that the impressive strength-to-weight ratio of the FDM Nylon 12CF is transformative for many industries from consumer goods and recreational goods to automotive and aerospace,” said Zehavit Reisin, VP, Head of Rapid Prototyping for Stratasys. “It enables designers to develop more practical and functional designs and get them to market faster, without worrying about how to prototype those parts using metal or molding.”

According to Tim Schniepp, Head of Tooling Solutions for Stratasys, “The very high stiffness-to-weight ratio of the FDM Nylon 12CF material makes it extremely well suited for a wide range of final part and manufacturing tooling applications where the combination of stiffness, strength and low weight is critical to the performance. Examples include drill guides, end- of- arm tooling, brackets, jigs, fixtures, and even metal forming tools.”

Expected to begin shipping in Q2 2017, FDM Nylon 12CF is available for the Stratasys Fortus 450mc Production 3D Printer and is compatible with soluble support SR-110. It requires an updated version of Insight software and a hardware upgrade. The material can produce parts in a layer thickness of 0.010 in (0.254 mm).

Agilus30: Improved Flexibility and Tear-Resistance

The Agilus30 family of materials, consisting of Agilus30 and Agilus30 Black, is created for designers and engineers that need to simulate flexible or rubber materials. The materials enable greater freedom to handle and test flexible parts and prototypes while delivering superior accuracy, fine details and enhanced product realism.

An excellent choice for modeling delicate parts that undergo repeated flexing and bending, the Agilus30 family’s all-around rubber-like performance and compatibility with soluble support (SUP706) is expected to be of interest to mechanical engineers, RP managers and industrial designers.

Examples of applications benefitting from Agilus30 include over-molding, soft-touch and living hinges, hoses, seals and gaskets, as well as knobs, grips, pulls, and handles. Agilus30 can also be combined with additional materials to create a wide range of Digital Materials with varying Shore A values, shades and colors.

Agilus30 is compatible with Stratasys’ Objet260/350/500 Connex1/2/3 3D Printing platforms and is now available for shipping.

>> Read more from Businesswire.com, March 7, 2017

Manufacturing Cars with Virtual Reality

Car manufacturers, such as General Motors and Ford, are increasingly using VR to test design plans, tolerances, and safety features in virtual environments to ensure their products are evaluated at a very early phase of the process, thereby reducing the time and costs.

VR has enabled them to shorten the vehicle development process in many ways. It enables the designers and engineers to view the products in 1:1 ratio in a real setting. It can actually turn around realistic models onto one scale within a day whereas if you were to build a physical prototype it would probably take up to a few weeks or months.

The use of virtual technologies allows designers and engineers to see, assess, and modify a considerable number of variants.

The use of virtual technologies allows designers and engineers to see, assess, and modify a considerable number of variants. (Image: General Motors)

The virtual data is displayed on a monitor, a large projection screen, or Cave Automatic Virtual Environment (CAVE) – an immersive virtual reality environment where projectors are directed to multiple walls of a room-sized cube.

The CAVE provides an environment where designers and engineers wear 3D glasses and become completely immersed in the computer-generated graphics of the exterior and interior of a vehicle. They can then evaluate mirrors, placement of controls, and design quality, such as gaps, fits, and finishes.  Although the CAVE really been around since the 1970s, there have been major upgrades recently.

Every program, vehicle, and platform utilizes VR at GM for decisions being made in the physical development process from the initiation of a program to a prototype.

Safety is another parameter being evaluated using VR. Using CAE crash and vehicle simulation data, you can optimize parts for weight strength and how they react under crash conditions. Ford also has a lab outfitted with VR technology to raise manufacturing quality.

In the future, VR tools will have a place in a meeting room to collaborate much the same as it used to be when engineers and designers would meet around the car down at the shop.

>> Read more by Chitra Sethi, ASME.org, March 2017

Industry 4.0 – Building the IIoT ecosystem the right way

Is Industry 4.0 just another buzz term that’s being hyped up by technology vendors with the aim of selling more products, or a legitimate trend that will transform sectors such as manufacturing in the months and years to come?

The evidence points to the latter. Industry 4.0, also referred to as the fourth industrial revolution, includes the heavy use of automation technologies and a greater exchange of data in manufacturing environments such as factories. Industry 4.0 got its name because it follows the earlier manufacturing phases of water/steam power, electric power and computing power.

The concept embraces technologies and delivery models such as cloud computing, big data/analytics, cyber-physical systems (CPS), robotics, augmented reality and the Internet of Things (IoT). In the age of Industry 4.0, manufacturing companies will be able to build and operate factories that are smarter than ever, so they can do things like easily customize products on demand from individual customers – something that is called Industrial IoT or IIoT.

Collaborative technologies

The technologies driving Industry 4.0 will often work in collaboration. For example, CPS is powered by cloud services, which enable intelligent objects and cloud-based programmatic modules to interact with each other.

New, smart factories will feature connected robots with access to big data/analytics capabilities, and technologies such as artificial intelligence, augmented reality, virtual reality, 3-D printing and other solutions will provide these facilities with agility, precision and efficiencies never seen before in a manufacturing environment.

As noted by management consulting firm McKinsey and Company, the concept of Industry 4.0 is more than just a flashy catchphrase. “A confluence of trends and technologies promises to reshape the way things are made,” the firm says.

Among these developments are a significant rise in data volumes, computational power, and connectivity; the advancements in data analytics and business intelligence (BI) capabilities; the availability of new forms of human-machine interaction; and enhancements in the ability to transfer digital instructions to the physical world, such as advanced robotics and 3D printing.

McKinsey has advised companies to closely watch Industry 4.0 developments so that they can leverage new opportunities made possible by Industry 4.0 technologies. It says the traditional manufacturing business model is being replaced by new models, and in order to reap the benefits of Industry 4.0 technologies businesses must prepare themselves for the coming digital transformation.

The platforms that support Industry 4.0 applications need to be open systems that can evolve with changing demands and market trends, and be able to quickly leverage whatever new technologies emerge in the coming years.

Factories of the future will be dynamic organisms that can be shaped and reshaped as need be, and they will be connected more so than ever with other entities such as customer service centers, companies that supply raw materials, distribution channels, etc.

Whereas today’s manufacturing environment typically consists of production plants with an incompatible mix of automation technologies that are not designed to share data with other manufacturing systems, smart factories will leverage IoT cloud platforms to gain a layer of cybernetic intelligence that sits on top of a company’s manufacturing operations.

Machine learning algorithms will be able to identify patterns and extract insights that can be used to optimize production operations. Predictive analytics will identify signs of system failures in one factory so that production can quickly be launched in other facilities.

In this modern environment, data from factories is delivered to the cloud, where it can be visualized and exposed to powerful analytics that provide higher layers of orchestration than ever for companies.

For example, there’s a large manufacturer based in the U.K.  that has factories all over the world. It’s looking to take all the data coming off of its factory automation platforms and all kinds of devices, some in real time, and place it into a common cloud layer to create customized views of all this data. That will allow the company to see across all its operations and create efficiencies not possible before.

One of the key drivers of the smart factory that will be enabled by IIoT and Industry 4.0 technologies is the push toward personalization in manufacturing. Instead of a factory churning out cookie-cutter versions of the same products at mass scale, it will be able to deliver highly customized products on a just-in-time basis the way a customer wants it.

Building the ecosystem

The potential of this future factory is not derived from what’s inside the enterprise, but outside. As beneficial as Industry 4.0 might prove to be for individual companies, executives in IT, operations and business need to look at this trend from a more holistic standpoint. They need to realize that the greatest returns will ultimately come from building an Industry 4.0 ecosystem that includes multiple market players involved in the process of designing, building, shipping and using products.

By linking together this ecosystem of partners in an Industry 4.0 environment, all of the individual components of the ecosystem are able to deliver greater value to the market. To put it in biological terms, instead of thinking in terms of individual cells it’s more about all the cells working together in a body, in a symbiotic relationship.

The Internet and specifically the cloud provide the framework necessary for organizations to work together more efficiently than ever, creating business and operational intelligence that can benefit partners within these interconnected business ecosystems.

One of the key technology components that will also enable the creation of Industry 4.0 partner ecosystems is application programming interfaces (APIs). Factories that expose APIs to partners will make it possible to create applications that work across a variety of systems.

To achieve this in an effective way, companies need to deploy an IoT platform such as Accelerite’s Concert that enables them to share service-oriented application APIs throughout their partner ecosystem in a managed platform as a service (PaaS) model. Applications will be quickly reconfigured by business analysts instead of programmers to account for different sources and types of data. Applications will be deployed in the cloud service that is most appropriate and efficient for the business, and easily adjust to accommodate for differences in cloud vendor-specific data ingestion, storage, distributed computing and machine learning APIs.

By leveraging the power of APIs and the cloud, companies will build and share a new generation of manufacturing-oriented IoT applications that will be at the heart of Industry 4.0 and IIoT, and that will provide not just greater intelligence and efficiencies but transformative new business models that industries have never seen before.

Building the smart factories that are capable of manufacturing the unique, highly personalized products consumers and businesses will be looking for is highly dependent on exploiting the full potential of Industry 4.0. A new class of API platform, designed for the latest revolution in manufacturing, is now emerging and will help companies to rapidly develop, manage and even monetize the products of the future.

While much of this sounds futuristic, IT and business executives need to be looking at these technologies now if they want to help prepare their organizations for what’s to come. If they don’t, they risk getting a late start in the dramatic shift to Industry 4.0.

This article was produced in partnership with Accelerite.

>> Our thanks to readwrite.com and their contributors for this re-posted article, March 1, 2017

2016 Breaks Records for North American Robot Orders and Shipments

The Robotic Industries Association (RIA), the leading advocate in North America for safety and innovation in robotics, announced today that in 2016 the North American robotics market broke all-time records for orders and shipments. During the year, 34,606 robots valued at approximately $1.9 billion were ordered in North America, representing growth of 10 percent in units over 2015. The automotive industry experienced another strong year with orders growing 17 percent. Units shipped to North American customers also grew by 10 percent, with 30,875 robots valued at $1.8 billion shipped in 2016. Shipments into the automotive market grew 25 percent relative to 2015.

Strength in Q4

The fourth quarter of 2016 alone saw North American orders of 10,621 robots valued at $561 million, a growth rate of 18 percent in units ordered and 21 percent in revenue over the fourth quarter of 2015. Q4 shipments grew 33 percent on a unit basis with shipments of 8,825 robots valued at $494 million.

“Automation played a vital role in spurring economic growth in North American manufacturing and services industries in 2016,” said Jeff Burnstein, President of A3. “We anticipate accelerated growth based on smarter, more connected and more collaborative robots in the coming years.”

Hottest Applications and Industries

Orders for robots spiked 61 percent in assembly applications and increased 24 percent in spot welding. The food and consumer goods industry increased orders for robots by 32 percent in 2016. Robots in these industries can be used in a variety of functions, including improving food safety, performing repetitive primary packaging tasks such as bin picking, tray loading and bottle handling, and assisting with secondary packaging tasks such as case packing, bundling, bagging and palletizing.

>> Read more by Robotics Industries Association, January 31, 2017