Article | December 21, 2021
Consumer demand has shifted dramatically in recent years, and manufacturers are trying to adapt to this shift. To maintain high product quality, minimize costs, and optimize supply chains, manufacturing analyticshas become essential for manufacturers.
Manufacturing analyticsis the process of gathering and analyzing data from various systems, equipment, and IoT devices in real-time to get essential insights.
As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity.
– Matt Mong
Manufacturing analyticscan assist in maintaining production quality, boost performance with high-profit returns, decrease costs, and optimize supply networks.
This article will outline manufacturing analyticsand present a list of possible application cases. It will also highlight the benefits of manufacturing analyticsfor any shop floor or factory.
Manufacturing analytics: An Overview
With manufacturing analytics, we can streamline and speed up the entire process. Data interchange and automation helps in speeding up the production process. Manufacturing analyticsuses predictive manufacturing, big data, Industrial IoT, network virtualization, and machine learningto produce better scalable production solutions.
Manufacturing analyticscollects and analyses data from many sources via sensors embedded in machinery to identify areas for improvement. Data is collected and presented in an easy-to-understand structure to illustrate where difficulties emerge throughout the process.
In short, manufacturing analyticscollects and analyses large volumes of data to reveal insights that might improve performance. Users can also obtain automated business reports to reply in real-time.
Why Manufacturing analytics is Vital for Leading Businesses
There are numerous benefits of manufacturing analyticsthat drive any company’s production and overall manufacturing business growth. The benefits of manufacturing analyticsfall into three distinct categories as below.
It reduces the overall cost: Analytics may save a significant amount of money if used more efficiently. Labor costs are also reduced due to automation and semi-autonomous machinery. Similarly, preventive and prescriptive maintenance programs may save money while enhancing productivity.
It boosts profits for businesses: Manufacturers can respond swiftly to changes in demand using real-time insights in production, inventory management, and demand and supply forecasting. For example, assume the data indicates that they are approaching their maximum capacity. In such instances, they can increase over time, increase capacity, modify procedures, or tweak other production areas to adapt and maintain delivery times.
Other unforeseen benefits: There are several advantages to the increased capabilities enabled by manufacturing analytics. These benefits include lower energy use, safer environmental practices, fewer compliance failures, and more customer satisfaction.
Five Real-world Applications of Manufacturing Analytics
A machine's analytics uses aggregate data from real-time detectors to anticipate when it needs to be replaced or functioning irregularly. This process helps predict machine failure or equipment defects.
Analytics can assist in determining a plant's capacity and how many products are produced by the unit in every production cycle, which is helpful in capacity planning. In addition, analytics may help determine the ideal number of units to create over time by considering capacity, sales predictions, and parallel schedules.
Predictive analytics solutions can automate maintenance requests and readings that shortens the procedure and reduce maintenance expenses.
Product development is an expensive process in manufacturing. As a result, businesses must invest in R&D to develop new product lines, improve existing models, and generate new value-added services.
Earlier, this approach was in place by repeated modeling to get the finest outcome. This approach can now be modeled to a large extent, with the help of data science and technologically superior analytics. Real-world circumstances can be replicated electronically using "digital twins" and other modeling approaches to anticipate performance and decrease R&D expenses.
Many factors that might help in the plan significant capital expenditures or brief breakdowns can be explained using historical data and a few high-impact variable strategies. For example, consider the seasonality of products like ice cream. As a result, historical market data and a few high-impact factors can help explain numerous variables and plan major capital expenditures or short-term shutdowns.
In addition to demand forecasting, predictive analytics incorporates advanced statistical techniques. With predictive analytics, a wide range of parameters, including customer buying behavior, raw material availability, and trade war implications, may be taken into consideration.
Warranty support may be a load for many manufacturers. Warranties are frequently based on a "one-size-fits-all" approach that is broader. This approach introduces uncertainty and unanticipated complications into the equation.
Products may be modified or updated to decrease failure and hence expense by using data science and obtaining information from active warranties in the field. It can also lead to better-informed iterations for new product lines to minimize field complaints.
Managing Supply Chain Risks
Data may be recorded from commodities in transit and sent straight from vendor equipment to the software platform, helping to enable end-to-end visibility in the supply chain.
Manufacturing analyticsallows organizations to manage their supply chains like a "control tower," directing resources to speed up or slow down. They may also order backup supplies and activate secondary suppliers when demand changes.
Businesses should adapt to changing times. Using analytics in manufacturinghas altered the business industry and spared it from possible hazards while boosting production lines. Industry 4.0's route has been carved. Manufacturing analyticsis the key to true Industry 4.0, and without it, the data produced by clever IoT devices is meaningless. The future is data-driven, and success will go to those who are ready to adopt it. The faster adoption, the sooner firms go ahead of the competition.
How can data analytics help manufacturers?
Data analytics tools can help manufacturers analyze machine conditions and efficiency in real-time. It enables manufacturers to do predictive maintenance, something they were previously unable to accomplish.
Why is data so crucial in manufacturing?
Data helps enhance manufacturing quality control. Manufacturers can better understand their company's performance and make changes by collecting data. Data-driven manufacturing helps management to track production and labor time, improve maintenance and quality, and reduce business and safety concerns.
What is Predictive Manufacturing?
Predictive manufacturing uses descriptive analytics and data visualization to offer a real-time perspective of asset health and dependability performance. In addition, it helps factories spot quality issues and takes remedial action quicker by eliminating the waste and the cost associated with it.
Article | October 20, 2021
Machine vision is becoming increasingly prevalent in manufacturing daily across industries. The machine vision manufacturing practice provides image-based automated inspection and analysis for various applications, including automatic inspection, process control, and robot guiding, often found in the manufacturing business.
This breakthrough in manufacturing technology enables producers to be more innovative and productive to meet customer expectations and deliver the best products on the market.
A renowned industry leader Mr. Matt Mongonce conveyed in an interview with Media7,
As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity
-Matt Mong, VP Market Innovation and Project Business Evangelist at Adeaca.
Why is Machine Vision so Critical?
The machine vision manufacturing process is entirely automated, with no human intervention on the shop floor. Thus, in a manufacturing process, machine vision adds significant safety and operational benefits. Additionally, it eliminates human contamination in production operations where cleanliness is critical.
For instance, the healthcare business cannot afford human contamination in some circumstances to ensure the safety of medicines. Second, the chemical business is prohibited from allowing individuals to come into touch with chemicals for the sake of worker safety. Thus, machine vision is vital in these instances, so it is critical to integrate machine vision systems into your production process.
Machine Vision Application Examples
To better understand how businesses are utilizing machine vision in production, we will look at five cases.
Even a few seconds of production line downtime might result in a significant financial loss in the manufacturing industry. Machine vision systems are used in industrial processes to assist manufacturers in predicting flaws or problems in the production line before the system failure. This machine vision capability enables manufacturing processes to avoid breakdowns or failures in the middle of the manufacturing process.
How is FANUC America Corporation Avoiding the Production Line Downtime with ROBOGUIDE and ZDT?
FANUC is a United States-based firm that is a market leader in robotics and ROBOMACHINE technology, with over 25 million units deployed worldwide. In addition, the company's professionals have created two products that are pretty popular in the manufacturing industry: ROBOGUIDE and ZDT (Zero Down Time).
These two standout products assist manufacturers in developing, monitoring, and managing production line automation. As a result, producers can enhance production, improve quality, and maximize profitability while remaining competitive.
Inspection of Packages
To ensure the greatest possible quality of products for their target consumer groups, manufacturers must have a method in place that enables them to inspect each corner of their product. Machine vision improves the manufacturing process and inspects each product in detail using an automated procedure.
This technology has been used in many industries, including healthcare, automation, and electronics. Manufacturers can detect faults, cracks, or any other defect in the product that is not visible to the naked eye using machine vision systems. The machine vision system detects these faults in the products and transmits the information to the computer, notifying the appropriate person during the manufacturing process.
Assembly of Products and Components
The application of machine vision to industrial processes involves component assembly to create a complete product from a collection of small components. Automation, electronics manufacturing, healthcare (medicine and medical equipment manufacturing), and others are the industries that utilize the machine vision system in their manufacturing process. Additionally, the machine vision system aids worker safety during the manufacturing process by enhancing existing safety procedures.
Manufacturers are constantly endeavoring to release products that are devoid of flaws or difficulties. However, manually verifying each product is no longer practicable for anybody involved in the manufacturing process, as production counts have risen dramatically in every manufacturing organization. This is where machine vision systems come into play, performing accurate quality inspections and assisting producers in delivering defect-free items to their target clients.
Earlier in the PCB penalization process, where numerous identical PCBs were made on a single panel, barcodes were used to separate or identify the PCBs manually by humans. This was a time-consuming and error-prone process for the electronics manufacturing industry. This task is subsequently taken over by a machine vision system, in which each circuit is segregated and uniquely identified using a robotics machine or a machine vision system. The high-tech machine vision system "Panel Scan" is one example of a machine vision system that simplifies the PCB tracing procedure.
The use of machine vision in the manufacturing business enables firms to develop more accurate and complete manufacturing processes capable of producing flawless products. Incorporating machine vision into manufacturing becomes a component of advanced manufacturing, which is projected to be the future of manufacturing in 2022. Maintain current production trends and increase your business revenue by offering the highest-quality items using a machine vision system.
What is the difference between computer vision and machine vision?
Traditionally, computer vision has been used to automate image processing, but machine vision is applied to real-world interfaces such as a factory line.
Where does machine vision come into play?
Machine vision is critical in the quality control of any product or manufacturing process. It detects flaws, cracks, or any blemishes in a physical product. Additionally, it can verify the precision and accuracy of any component or part throughout product assembly.
What are the fundamental components of a machine vision system?
A machine vision system's primary components are lighting, a lens, an image sensor, vision processing, and communications.
"name": "What is the difference between computer vision and machine vision?",
"text": "Traditionally, computer vision has been used to automate image processing, but machine vision is applied to real-world interfaces such as a factory line."
"name": "Where does machine vision come into play?",
"text": "Machine vision is critical in the quality control of any product or manufacturing process. It detects flaws, cracks, or any blemishes in a physical product. Additionally, it can verify the precision and accuracy of any component or part throughout product assembly."
"name": "What are the fundamental components of a machine vision system?",
"text": "A machine vision system's primary components are lighting, a lens, an image sensor, vision processing, and communications."
Article | December 10, 2021
IoT in the manufacturing industry introduces a superior technology that is coming up as a blessing for the industry. Manufacturers are enjoying one-of-a-kind benefits and returns on their reinvestments in IoT. Benefits such as enhanced productivity, work safety, reduced downtime, cost-effective operations, and more such benefits of IoT in manufacturing make it more and more popular with each passing day.
The global IoT market is estimated to reach a value of USD 1,386.06 billion by 2026 from USD 761.4 billion in 2020 at a CAGR of 10.53 percent over the forecast period of 2021-2026. So the whole worldwide market of IoT has a bright future in the following years.
“As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity.”
– Matt Mong, VP Market Innovation and Project Business Evangelist at Adeaca
Let’s check out below some exciting facts about IoT in manufacturing and see how IoT makes a difference in the manufacturing industry.
IoT in Manufacturing: Some Interesting Facts
According to PwC, 91% of industrial/manufacturing enterprises in Germany invest in "digital factories" that use IoT solutions.
According to the International Federation of Robotics (IFR), China employs more industrial robots than any other country (many of which are connected to the internet in some way).
According to IoT Analytics, the industrial sector spent more than $64 billion on IoT in 2018 and expects investment in Industry 4.0 to reach $310 billion by 2023.
According to the Eclipse Foundation, most IoT developers are focused on developing smart agriculture systems (26%), while industrial automation is another big focus area (26%). However, home automation is dwindling in popularity, accounting for just 19% of projects.
How Does IoT Work for the Manufacturing Industry?
The Internet of Things (IoT) is a network of interconnected devices that communicate with one another and with other networks. While IoT-enabled devices are capable of various tasks, they are primarily employed to collect data and carry out specific tasks. The implementation of the Internet of Things in manufacturing is often referred to as the IIoT, or Industrial Internet of Things.
IoT makes use of 'smart' devices to collect, process, and act on data. These intelligent devices are equipped with sensors and other software that enable them to communicate and exchange data inside the network.
IoT-enabled equipment gives crucial real-time data that enables manufacturers or machine operators to make informed decisions. So, how does it function in practice?
Sensors capture data from the system and transfer it to the cloud, where it can be analyzed.
The data is transferred to the quality assurance system.
The data that has been analyzed is forwarded to the end-user.
How the IoT is Improving Manufacturing Business Operations
The Internet of Things (IoT) has numerous benefits for the manufacturing industry. We'll go over some of the significant benefits that the Internet of Things brings to the manufacturing business.
Energy Efficiency Solutions
Energy is a high cost in manufacturing. Unfortunately, the current industrial energy infrastructure can only track excessive energy consumption.
The utility bills include the factory's energy consumption records. But, unfortunately, nobody can break down energy consumption to the device level and find out the underperforming pieces. Some energy usage monitoring tools exist, but they only provide partial data, making system analysis difficult.
IoT can help by giving device-level energy data. The sensors will detect any underperforming devices in the network and alert you so you can take action. As a result, the technology can help you reduce energy waste and find other ways to save it.
Data is required to determine trends and quality of production at a manufacturing facility. It also helps manufacturers plan and anticipates changes. These forecasts can help with inventory management, employment, cost control, and other operational procedures. Thus, IoT technology makes it easier to foresee and optimize customer requirements.
The Internet of Things (IoT) uses sensors to gather data about assets' health and productivity. In addition, it uses advanced analytics to give actionable information. These are presented on an appealing dashboard connected to your smart device. This allows for predictive maintenance to be used in the manufacturing industry.
Superior Product Quality
Every manufacturer is determined to produce a high-quality product at a low cost. Therefore, a minor quality modification can have a significant influence on the manufacturing firm.
Customer happiness, waste reduction, sales, and profit can all benefit from high-quality products. But making high-quality products isn't easy.
The Internet of Things (IoT) can assist you in this endeavor. Poorly set, calibrated, and maintained equipment are some of the main reasons for low-quality products. Worst of all, many small things sometimes go ignored as the final product seems perfect. Quality tests show the product is fine, but your consumers start having problems after a couple of months.
Imagine the resources needed to identify and correct the problem. Sensors in an IoT network detect even minimal tweaks in setup and alert operators. The team might momentarily stop production to address the issue before the production cycle gets complete.
Rapid and Informed Decision-Making
The IoT can dramatically improve organizational decision-making. It unlocks vital data about network equipment performance and delivers it to the right person.
Managers and field operators can use this data to improve plant processes and overall production.
In addition to these significant benefits, IoT in manufacturing can help manufacturers improve their manufacturing operations and construct a unit that meets the vision of the smart factory of 2040. The future beyond IoT would be the icing on the cake for all of us, as technology has always amazed us.
Imagine the day when IoT and AI merge, and the virtual gadgets controlled by IoT are the next major milestone. Then, the ideal combination of robotics, AI, and VR may reduce the manufacturing plant size and cost while increasing the output to a level that is unimaginable and unattainable as of now.
Airbus Improved Production Efficiency with Its Factory of the Future Concept
It's a massive task for a commercial airliner to be assembled. The expense of making a mistake throughout making such a craft can be significant, as there are millions of parts and thousands of assembly phases. Airbus has established a digital manufacturing effort called Factory of the Future to optimize operations and increase production capacity. The company has installed sensors on factory floor tools and machinery and supplied workers with wearable technologies, such as industrial smart glasses, to reduce errors and improve workplace safety. The wearable allowed for a 500% increase in efficiency while eliminating nearly all mistakes in one process named cabin seat marking.
While the benefits of IoT devices have long been a topic of discussion among technology enthusiasts, the incorporation of IoT in manufacturing is creating a new buzz in the industry. The benefits of IoT in manufacturing, such as remote analysis of operations, processes, and products, are assisting manufacturers in establishing a more productive manufacturing unit. As a result of these benefits, IoT use in manufacturing is accelerating. Recognize the IoT's potential and take a step toward incorporating it into your manufacturing operation in 2022.
What is the Industrial Internet of Things (IIoT)?
IIoT stands for Industrial Internet of Things. It uses data to improve industrial efficiency. To enhance industrial performance, it uses embedded sensors, cloud data, and connected devices.
Why is the IoT changing manufacturing?
Real-time monitoring of machines and accurate reporting for better decisions are possible through IoT. This improves business strategies and project control. Thus, the Internet of Things has a significant impact on the profitability of any manufacturing company.
How does the IoT transform the way we do business?
We can use data collected by IoT devices to improve efficiency and help organizations make better decisions. They tell organizations the truth, not what they hope or believe.
"name": "What is the Industrial Internet of Things (IIoT)?",
"text": "IIoT stands for Industrial Internet of Things. It uses data to improve industrial efficiency. To enhance industrial performance, it uses embedded sensors, cloud data, and connected devices."
"name": "Why is the IoT changing manufacturing?",
"text": "Real-time monitoring of machines and accurate reporting for better decisions are possible through IoT. This improves business strategies and project control. Thus, the Internet of Things has a significant impact on the profitability of any manufacturing company."
"name": "How does the IoT transform the way we do business?",
"text": "We can use data collected by IoT devices to improve efficiency and help organizations make better decisions. They tell organizations the truth, not what they hope or believe."
Article | December 6, 2021
Additive Manufacturing (AM) uses computer-aided design (CAD) or 3D object scanners to create accurate geometric features. In contrast to traditional manufacturing, which frequently involves milling or other processes to eliminate superfluous material, these are produced layer by layer, as with a 3D printing process.
The global additive manufacturing market is expected to grow at a 14.42 percent annual rate from USD 9.52 billion in 2020 to USD 27.91 billion in 2028, according to reports and data. Overall, the worldwide 3D printing industry is gaining traction due to various reasons, some of which are listed below.
Significantly, greater resolution
Reduced manufacturing costs as a result of recent technology breakthroughs
Ease of creating customised goods
Increasing possibilities for printing with diverse materials
Funding by the government for 3D printing ventures
Additive manufacturing is available or may be implemented in various procedures, which is the primary objective of this article. First, we'll look at the seven additive manufacturing processes and which one is the best to use. So let us begin.
“Don’t be afraid to go outside of your industry to learn best practices. There might be something that surprises you or inspires you to try in your line of work.”
– Emily Desimone, Director of Global Marketing at SLM Solutions
Additive Manufacturing Processes
There are numerous diverse additive manufacturing processes, each with its own set of standards. Here are the seven additive manufacturing procedures that many manufacturers consider based on their benefits from each process, or whichever approach best suits their product requirements.
This additive manufacturing process is quite similar to that of conventional inkjet printers, in which material droplets are selectively placed layer by layer to build a three-dimensional object. After completing a layer, it is cured with UV radiation.
VAT Photo Polymerization
This procedure employs a technology called photo polymerization, in which radiation-curable resins or photopolymers are utilized to ultraviolet light to generate three-dimensional objects selectively. When these materials are exposed to air, they undergo a chemical reaction and solidify. Stereo lithography, Digital Light Processing, and Continuous Digital Light Processing are the three primary subcategories.
Binder jetting is a process that deposits a binding agent, typically in liquid form, selectively onto powdered material. The print head deposits alternating layers of bonding agent and construction material and a powder spreader to create a three-dimensional object.
S. Scott Crump invented and patented material extrusion in the 1980s using Fused Deposition Modeling (FDM). The continuous thermoplastic filament is fed through a heated nozzle and then deposited layer by layer onto the build platform to produce the object.
Powder Bed Fusion
Powder bed fusion procedures, particularly selective laser sintering, were the pioneers of industrial additive manufacturing. This approach melts the powdered material and fuses it using a laser or electron beam to form a tangible item. The primary kinds of powder bed fusion are direct metal laser sintering, selective laser sintering, multi-jet fusion, electron beam melting, selective laser melting, and selective heat sintering.
Sheet lamination is a catch-all term encompassing ultrasonic additive manufacturing, selective deposition lamination, and laminated object manufacturing. All of these technologies stack and laminate sheets of material to form three-dimensional objects. After the object is constructed, the parts' undesirable areas are gradually removed layer by layer.
Directed Energy Deposition
Directed energy deposition technology employs thermal energy to melt and fuse the materials to form a three-dimensional object. These are pretty similar to welding processes, but are much more intricate.
Which Additive Manufacturing Process is best? Why?
Based on three fundamental factors, additive manufacturing techniques are categorized into seven types. First, the way material is solidified is determined first by the type of material employed, then by the deposition technique, and finally by how the material is solidified.
The end-user often chooses an additive manufacturing technique that best suits his requirements, followed by the explicit material for the process and application, out of the seven basic additive manufacturing processes.
Polymer materials are commonly used in AM techniques because they are adaptable to various procedures and can be modified to complicated geometries with high precision. Carbon-based compounds are used to strengthen polymers. Polymers, both solid and liquid, have been widely used due to the variety of shapes, formability, and end-use qualities available. Wherever the light-activated polymer contacts the liquid's surface, it instantly solidifies.
Photo polymerization, powder bed fusion, material jetting, and material extrusion are the most common additive manufacturing procedures for polymers. The materials employed in these processes can be liquid, powder, or solid (formed materials such as polymer film or filament).
How BASF is Using Additive Manufacturing
BASF is a chemical company. BASF, one of the world's major chemical companies, manufactures and provides a range of 3D printing filaments, resins, and powders within its extensive material portfolio.
The company, well-known in the 3D printing sector, has formed major material agreements with several 3D printer manufacturers, including HP, BigRep, Essentium, BCN3D, and others.
BASF went even further in 2017 by establishing BASF 3D printing Solutions GmbH (B3DPS) as a wholly-owned subsidiary to expand the company's 3D printing business. In addition, BASF stated last year that B3DPS would change its name to Forward AM.
BASF's role in the 3D printing business, however, is not limited to material development. BASF has made several investments in 3D printing companies over the years, including the acquisition of Sculpteo, one of the significant French 3D printing service bureaus, last year.
BASF sees 3D printing as having a bright future. With the growing popularity of professional 3D printers, all of these systems will eventually require robust, high-quality polymer materials to perform at their best – and BASF has been paving the way to becoming one of the leading solution providers.
All additive manufacturing procedures are unique and helpful in their way. Still, some have additional advantages over others, such as the material used, highresolution, precision, and the ability to build complicated parts. Because of these added benefits, photopolymerization, material jetting, powder bed fusion, and material extrusion are preferred over others. Therefore, choose the AM process that is best suited to your manufacturing business and will assist you in achieving the desired final product output.
What are the benefits of additive manufacturing?
AM enables manufacturers to reduce waste, prototyping costs, and customization while conserving energy and increasing production flexibility. Additionally, it benefits the supply chain and the environment, encouraging businesses to increase their manufacturing sustainability.
What is the major challenge in additive manufacturing?
Many businesses are struggling with the current difficulty of producing large and odd-sized parts using additive manufacturing. So, this can be considered a significant challenge in additive manufacturing.
What are the steps of additive manufacturing?
The additive manufacturing steps are divided into four steps as below,
Step1 - Design a model with CAD software
Step4 - Post-processing
"name": "What are the benefits of additive manufacturing?",
"text": "AM enables manufacturers to reduce waste, prototyping costs, and customization while conserving energy and increasing production flexibility. Additionally, it benefits the supply chain and the environment, encouraging businesses to increase their manufacturing sustainability."
"name": "What is the major challenge in additive manufacturing?",
"text": "Many businesses are struggling with the current difficulty of producing large and odd-sized parts using additive manufacturing. So, this can be considered a significant challenge in additive manufacturing."
"name": "What are the steps of additive manufacturing?",
"text": "The additive manufacturing steps are divided into four steps as below,
Step1 - Design a model with CAD software
Step2 - Pre-processing
Step3 - Printing
Step4 - Post-processing"