Article | December 10, 2021
A new form of robot is entering manufacturing plants all around the globe. Instead of being locked away in their own work cell, collaborative robots work side by side with their human counterparts. Together, they form the manufacturing crew of the future.
Collaborative robots, or cobots, are more flexible, easy to use, and safer than industrial robots. Instead of ending up abandoned in a corner, they are proving to be serious expansions of production capacity leading to better ways of creating superior quality products.
1.1 A New Breed of Bot
Cobots are a new type of automation product with their own ISO standards for safety and usability. For a robot to qualify as a cobot, it has to be used for tasks of a collaborative nature while sharing all or part of its reach space with human operators. So it is not the product alone that classifies it as a cobot.
Industrial robots must be expertly programmed for one specific job along the production line. This requires hard line coding and endless tweaking and testing, which together with other factors make for a sizable upfront investment. Not so with collaborative robots.
Cobots may look similar to traditional robots in some ways, but they are much easier to install and program. This foregoes the need to cooperate with a robotic integration service. Their lightweight and friendly form factor lets manufacturers conveniently relocate them on the shopfloor from one project to another.
This renders the robotics technology perfect for a data-driven, Industry 4.0 work environment. Cobots can side with traditional machinery and additive manufacturing equipment, aided by artificial intelligence and cloud connectivity while embedded in a networked environment rich with smart sensors and mixed reality interfaces.
1.2 A Unique Blend of Benefits
Because it is fairly straightforward to reprogram a cobot to various tasks, they are perfect for high-mix, low-volume work to meet the rising demand for ultra-customized products.
They can also do multiple tasks in unison, such as alternatingly loading a machine and finishing parts from the previous cycle. Here are some other advantages in addition to flexibility:
• Low investment. Cobots typically cost a fraction of the price of an industrial robot, but they offer much lower payload and reach. ROI is typically one to two years.
• Safety. With rounded surfaces, force-limited joints, and advanced vision systems, cobots are exceptionally safe. This reduces the risk of injury due to impact, crushing, and pinching. Driverless transport systems are wheeled mobile robots that immediately halt when their lasers detect the presence of a nearby human being.
• Accuracy. Cobots score well on accuracy with 0.1mm precision or well below that. While they do typically sacrifice speed, dual-mode cobots can be converted to fully-fledged tools of mass production that run at full speed in their own safeguarded space.
• Easy to program. Many brands offer user-friendly programming interfaces from beginner to expert level. This reduces the need for continuous availability of expensive and scarce expertise while giving current employees an incentive to upskill. And because they can be deployed within hours, cobots can be leased for temporary projects.
• Research. Small processing plants, agile start-ups, and schools can invest in cobots to experiment with ways to automate processes before committing to full automation.
1.3 Cobot Activity Repertoire
Cobots are perfect candidates for taking over strenuous, dirty, difficult, or dull jobs previously handled by human workers. This relieves their human co-workers from risk of repetitive strain injury, muscle fatigue, and back problems. They can also increase job satisfaction and ultimately a better retirement.
The cobot’s program of responsibilities includes:
• Production tasks such as lathing, wire EDM, and sheet stamping.
• Welding, brazing, and soldering.
• Precision mounting of components and fasteners, and applying adhesive in various stages of general assembly.
• Part post-finishing such as hole drilling, deburring, edge trimming, deflashing, sanding, and polishing.
• Loading and unloading traditional equipment such as CNC and injection molding machines, and operating it using a control panel to drastically reduce cycle times.
• Post-inspection such as damage detection, electronic circuit board testing, and checking for circularity or planarity tolerances.
• Box-packing, wrapping, and palletizing.
• Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) assist with internal transport and inventory management.
1.4 No-Code Programming
While an industrial robot requires the attention of a high-paid robotics engineer, anyone with basic programming savviness can install and maintain a collaborative unit.
Brands are releasing more and more kits for quick installation and specific use cases. Instead of being all numbers and line-coding, current user interaction is exceptionally people-focused.
At the lowest skill level, lead-through programming lets operators physically guide the cobot’s end-of-arm-tool (EOAT) through the desired motion path, after which it will flawlessly replicate the instructed behaviour.
It is also possible to enter desired waypoints as coordinates. At the highest level, it is of course still possible to have full scripting control.
An intermediate step is visual programming interfaces. These let users create blocks of functionality that they can string together into more advanced action sequences, while entering the appropriate parameters for each function such as gripping strength, screwing tightness, or pressing force.
These UIs come in the form of in-browser or mobile apps.
Based on a 3D-CAD model of the machine and its industrial environment, a digital twin of the cobot can simulate and optimize its operations, for example to prevent collisions.
It also lets operators remotely monitor and adjust the machine while it’s running. All the while, back-end artificial intelligence can do its analyses to find further efficiency improvements.
3D models of the to-be-manufactured product can be imported for edge extraction of complex surfaces. These will then be converted into the cobot’s desired movement trajectories instead of tedious manual programming.
This makes them feasible to implement for highly dexterous tasks like welding curved hydroformed metal parts or sanding and polishing the most intricate of 3D printed geometries.
Interfacing directly with the robot is becoming increasingly human-centered as well. Future cobots will respond to voice interaction as well as touch input, eradicating the screens-and-buttons paradigm of current devices.
Some brands are giving the cobot a face with emotional expressions, hoping to lower the barrier to adoption. The upcoming generation of cobots can even respond to body language, as well as show its intentions by projecting light to where they are about to reach or move next.
1.5 A Human World
Ultimately, the objective of any company is to create value for people. It is not an option to completely remove humans from the shop floor in an attempt to stay at the forefront of innovation.
Attempting to leap to full automation and the utopian “lights-out factory” does not work anyway, as automotive giants such as Ford, Chrysler, GM, and Tesla can testify. A significant portion of human employees will indeed need to give up their roles. On the other hand, improved productivity levels open up space to retain personnel and uplift them to more creative, managerial, analytical, social, or overall more enjoyable jobs.
For certain tasks, humans still need to be kept inside the manufacturing loop. For example:
• Complex assembly routines and handling of flexible components.
• Large vehicle subassemblies contain many variable components and require more hand-eye coordination than one cobot can handle. Humans are needed to make sure everything lands in the right position while the cobot provides assistive muscle power.
• Fashion, footwear, jewellery, art pieces, and other products where creation borders on artistry rather than mechanical assembly require the aesthetic eye of humans. People are also needed to spot aesthetic deficiencies in custom one-offs in order to correspond with customers before finishing the production batch.
• While intelligent automation software can spot bottlenecks in efficiency, humans are required for creative problem solving and context-awareness to make decisions. A spirit of flexibility and innovation is just as important as the accuracy of perfect repetitions.
1.6 Mission: Install a Cobot
Cobots have numerous advantages over industrial solutions or people-only workspaces. They enable faster, more precise, and more sophisticated operations while reducing downtime and maintaining employee satisfaction.
Low-voltage operation and reduced material waste fits with sustainable innovation and corporate social responsibility programs.
Many companies are reporting surges in production capacity and staff generally experience the presence of cobots as favorable. For example, industry leviathans like BMW and Mercedes-Benz are reaching the conclusion that in many parts of the production process implementing a cobot has been the right decision.
Connecting all parts of the production line with full automation solutions is a pipedream. It works only when all steps are perfectly attuned, and in reality this never happens and one misstep can be catastrophic.
Whether to hire a human, a robot, or a co-robot is a complex and ever-more pressing decision. Statistical process control is paramount for large organizations to make unbiased data-driven decisions.
Determine the key performance indicators, then find the most critical bottlenecks and major opportunities for leaps in production efficiency, product quality, or staff unburdening.
Talk to employees for their insights and probe their level of skill and enthusiasm needed for working with their new artificial assistants. Digital transformation should be an exciting shift in the organization and its people, so apply new technological advancements only where it makes sense.
Despite common beliefs about robotization, the cobot is an entirely separate product category that can be a surprisingly plug-and-play solution for simple tasks, with programming apps becoming increasingly intuitive.
A cobot’s flexibility makes it perfect to run early experiments to help companies find its best spot on the factory floor. Its unbelievable precision, consistency, and level of control generally can make a strong first impression on customers.
Not only can cobots increase production capacity while reducing idle time and cycle time to accelerate manufacturing across many vertical markets, but they also enrich the work environment resulting in happier and more involved employees.
For many companies, a cobot can be the next logical step in their digital transformation.
Article | December 8, 2021
A digital twin is a virtual model of an object or system that comprises its lifecycle. It is updated with real-time data and aids decision-making through simulation, machine learning, and reasoning for the production system.
IoT sensor data from the original object is used to create a digital twin of the system. This cloud-connected data allows engineers to monitor systems and model system dynamics in real-time.
Modifications can be tested on the digital twin before making changes to the original system.
Considering that digital twins are supposed to replicate a product's complete lifecycle and are used throughout the production process, it's not unexpected that digital twins have become prevalent in all stages of manufacturing.
“More than a blueprint or schematic, a digital twin combines a real-time simulation of system dynamics with a set of executive controls,”
– Dr. Daniel Araya, consultant and advisor with a special interest in artificial intelligence, technology policy, and governance
Companies will increasingly embrace digital twins to boost productivity and decrease expenses. As per recent research by Research and Markets, nearly 36% of executives across industries recognize the benefits of digital twinning, with half planning to implement it by 2028.So how does this digital twin technology benefit modern manufacturing? Let's have a look.
How the Digital Twin Drives Smart Manufacturing
Digital twins in manufacturing are used to replicate production systems. Manufacturers can develop virtual representations of real-world products, equipment, processes, or systems using data from sensors connected to machines, tools, and other devices.
In manufacturing, such simulations assist in monitoring and adapting equipment performance in real-time. With machine learning techniques, digital twins can predict future events and anticipate potential difficulties.
For maintenance, digital twins allow for quick detection of any problems. They collect real-time system data, prior failure data, and relevant maintenance data. The technique employs machine learning and artificial intelligence to predict maintenance requirements. Using this data, companies can avoid production downtime.
Digital Twin and Artificial Intelligence (AI) in manufacturing
Using digital twins and AI in production can enhance uptime by predicting potential failures and keeping equipment working smoothly. In addition, there are significant cost savings in the planning and design process as digital twins and AI can be used to replicate a specific scenario.
Maintenance is another area that has seen significant progress with the use of digital twin manufacturing. A Digital Twin powered by AI can predict when a piece of equipment will fail, allowing you to arrange predictive maintenance that is not simply taking information from OEM manuals but can significantly cut maintenance expenses along with reducing downtime.
Using the digital twin, it is feasible to train virtual workers in high-risk functions, similar to how pilots are trained using flight simulators. It also frees up highly skilled workers to upgrade the plant and streamline operations.
General Electric Created the Most Advanced Digital Twin
General Electric Company (GE) is a multinational business based in Boston that was founded in 1892. It has developed the world's most advanced digital twin, which blends analytic models for power plant components that monitor asset health, wear, and performance with KPIs (Key Performance Indicators) determined by the customer and the organization's objectives. The Digital Twin is powered by PredixTM, an industrial platform built to manage huge amounts of data and run analytic algorithms. General Electric Company provides extra "control knobs" or "dimensionality" that can be utilized to improve the operation of the system or asset modeled with GE Digital Twin.
Given the numerous advantages of digital twin manufacturing, the potential for digital twins to be used in manufacturing is virtually endless in the near future. There will be a slew of new advancements in the field of digital twin manufacturing. As a result, digital twins are continually acquiring new skills and capabilities. The ultimate goal of all of these enhancements is to create the insights necessary to improve products and streamline processes in the future.
What is a digital twin in manufacturing?
The digital twins could be used to monitor and enhance a production line or perhaps the whole manufacturing process, from product design to production.
How digital twin benefit manufacturers?
Using digital twins to represent products and manufacturing processes, manufacturers can save assembly, installation, and validation time and costs.
What is a digital thread?
A digital twin is a realistic version of a product or system that replicates a company's equipment, controls, workflows, and systems. The digital thread, on the other hand, records a product's life cycle from creation to dissolution.
"name": "What is a digital twin in manufacturing?",
"text": "The digital twins could be used to monitor and enhance a production line or perhaps the whole manufacturing process, from product design to production."
"name": "How digital twin benefit manufacturers?",
"text": "Using digital twins to represent products and manufacturing processes, manufacturers can save assembly, installation, and validation time and costs."
"name": "What is a digital thread?",
"text": "A digital twin is a realistic version of a product or system that replicates a company's equipment, controls, workflows, and systems. The digital thread, on the other hand, records a product's life cycle from creation to dissolution."
Article | November 20, 2021
Modern manufacturing methods are pioneering and adopting manufacturing industry advancements. To remain competitive in the present era and provide the most excellent industry solutions to your organization and target customer group in 2022, you must employ new manufacturing technologies in your manufacturing processes.
Additionally, embracing current technologies is the ideal approach to tackle the industry's current challenges such as workplace safety, digitalization of operations, and a lack of skilled workers.
This article will discuss some of the leading manufacturing technologies that transform traditional manufacturing facilities into smart manufacturing factories. So, let us begin.
Manufacturing Technology & Innovations for 2022
To better understand industry 4.0, let's look at some of the manufacturing technologies that will dominate the manufacturing industry in 2022.
Numerous industries, including aerospace, healthcare, electronics, and architecture, utilize 3D printing in manufacturing. It is the most widely used technology across industries and will remain so in 2022 and in the years to come.
We may also anticipate more advancements in this technology to help overcome current barriers to 3D printing adoption, including equipment costs, material constraints, lengthier manufacturing times, a lack of knowledge, and legal issues.
Additionally, it would assist manufacturers in overcoming current manufacturing challenges such as increasing product demand, increasing automation, and locating and retaining the workforce in manufacturing plants. It is vital to incorporate 3D technology into production processes to achieve greater precision and accuracy in manufacturing.
The Internet of Things is a critical component of the industry 4.0 revolution. It has altered the environment of data collection and analysis across sectors. For example, the Internet of Things is assisting manufacturers in better understanding manufacturing and supply chain operations, forecasting product demand, and boosting customer experiences.
Implementing IoT in your manufacturing plant will also help you avoid production delays and increase the performance of your production lines. Additionally, it will decrease equipment downtime and improve process efficiency. It also enhances worker safety and enables more effective labor management.
To begin implementing IoT in your manufacturing plant, you must first examine your manufacturing processes and research how other organizations have implemented IoT in their manufacturing processes or products. This method will assist you in determining the optimal location to begin integrating the IoT in your manufacturing plants and transforming them into smart ones.
“Once you start to look at yourself in the right way and realize that projects are at the core of your business, it is easy to see how you should use technology to support your business.”
– Matt Mong, VP of Market Innovation and Project Business Evangelist at Adeaca.
GD & T
The model created in the CAD program for any product is not exactly replicated with the exact dimensions during the production procedures. Thus, manufacturers or engineers utilize GD&T (Geometric Dimension &Tolerancing) to manage and communicate the permissible variation within a product assembly to manufacturing partners and inspectors.
GD&T is a programming language that enables developers and inspectors to optimize functionality without incurring additional costs. The primary advantage of GD&T is that it expresses the design intent rather than the final geometry. However, as with a vector or formula, it is a representation of the actual item.
AR & VR
The two primary transformation aspects in the industry 4.0notion are augmented reality (AR) and virtual reality (VR). AR technology in manufacturing enables firms to operate more efficiently by reducing production time. Additionally, it discovers and resolves manufacturing process difficulties.
Virtual reality technology benefits the industrial business in a variety of ways. It enables product designers to mimic their prototypes or models using powerful virtual reality software. This enables them to correct faults at the first stage of production and minimize production time and cost. Additionally, the technology provides additional benefits, such as increased workplace productivity and safety.
Enterprise Resource Planning (ERP) refers to a comprehensive end-to-end software solution that is used across sectors. It assists the manufacturing business in successfully maintaining production processes and other operational data by avoiding numerous roadblocks along the way. ERP technology enables enterprises to improve process efficiency and product quality by tackling industry-specific difficulties such as insufficient data, operation integration, inventory control, supply chain management, and on-time delivery.
Discover How John Deere Manufactured Their Tractors Using Cutting-edge Technologies
John Deere is a significant firm that embraces innovation and the Internet of Things. The company integrates Internet of Things sensors, wireless communication, and intelligent land management systems. It further integrates IoT tools into its manufacturing process, bridging the gap between technologies. Additionally, the company is a pioneer in GPS technology. Its most modern technology, which it incorporates into tractors, is accurate to within two centimeters. Additionally, the organization has implemented telemetry technology for predictive maintenance.
Manufacturing innovations are assisting manufacturers in modernizing their traditional manufacturing processes. Modern manufacturing is equipped with modern technologies that aim to improve the processes and goods, increasing the manufacturers' commercial revenues. So, to remain competitive in this age of technological innovation, manufacturers must update their manufacturing processes to remain relevant in today's manufacturing world.
What is manufacturing innovation?
Manufacturing innovation includes new technology, supply chain modifications, and product and process improvements. As a result, businesses can benefit significantly from innovation and typically surpass their competitors.
Which technologies are considered to be a component of advanced manufacturing?
3–D printing, robotics, IoT, nanotechnology, cloud computing, robotics, and big data are the significant components of advanced manufacturing.
How are cutting-edge technologies assisting the manufacturing sector?
The cutting-edge technology can precisely estimate demand to set production objectives, analyze machine data to predict when parts will break before a human operator can detect, and more.
"name": "What is manufacturing innovation?",
"text": "Manufacturing innovation includes new technology, supply chain modifications, and product and process improvements. As a result, businesses can benefit significantly from innovation and typically surpass their competitors."
"name": "Which technologies are considered to be a component of advanced manufacturing?",
"text": "3–D printing, robotics, IoT, nanotechnology, cloud computing, robotics, and big data are the significant components of advanced manufacturing."
"name": "How are cutting-edge technologies assisting the manufacturing sector?",
"text": "The cutting-edge technology can precisely estimate demand to set production objectives, analyze machine data to predict when parts will break before a human operator can detect, and more."
Article | January 4, 2022
So much emphasis has been placed on features, advantages, and benefits; too little attention has been paid to delivery dates. The best automation solution on paper means nothing if it cannot be delivered in 2022. Selling the sexy sizzle of new, clever, even remarkable AGVs means nothing if manufacturers and distribution centers cannot take delivery of the product until 2023. Throughout industrial manufacturing and distribution the lead time from many AGV manufacturers is more than a year. That means product ordered in Q1 2022 will not be delivered until the following year. That is an absurd lead time and reflects poor planning and unnecessary supply chain constraints.