Article | December 16, 2021
Computer-aided manufacturing (CAM) is a technology that revolutionized the manufacturing business. Pierre Bézier, a Renault engineer, produced the world's first real 3D CAD/CAM application, UNISURF CAD. His game-changing program redefined the product design process and profoundly altered the design and manufacturing industries.
So, what is CAM in its most basic definition?
Computer-aided manufacturing (CAM) is the application of computer systems to the planning, control, and administration of manufacturing operations. This is accomplished by using either direct or indirect links between the computer and the manufacturing processes. In a nutshell, CAM provides greater manufacturing efficiency, accuracy, and consistency.
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
In light of the numerous advantages and uses of computer-aided manufacturing, manufacturers have opted to use it extensively. The future of computer-aided manufacturing is brightening due to the rapid and rising adoption of CAM.
According to Allied Market Research, the global computer-aided manufacturing market was worth $2,689 million in 2020 and is expected to reach $5,477 million by 2028, rising at an 8.4% compound annual growth rate between 2021 and 2028.
Despite all this, each new development has benefits and challenges of its own. In this article, we'll discuss the benefits of CAM, the challenges that come with it, and how to deal with them. Let's start with the advantages of computer-aided manufacturing.
Benefits of Computer Aided Manufacturing (CAM)
There are significant benefits of using computer-aided manufacturing (CAM). CAM typically provides the following benefits:
Increased component production speed
Maximizes the utilization of a wide variety of manufacturing equipment
Allows for the rapid and waste-free creation of prototypes
Assists in optimizing NC programs for maximum productivity during machining
Creates performance reports automatically
As part of the manufacturing process, it integrates multiple systems and procedures.
The advancement of CAD and CAM software provides visual representation and integration of modeling and testing applications.
Greater precision and consistency, with similar components and products
Less downtime due to computer-controlled devices
High superiority in following intricate patterns like circuit board tracks
Three Challenges in CAM and Their Solutions
We have focused on the three primary challenges and their solutions that we have observed.
Receiving Incomplete CAD Updates
Receiving insufficient CAD updates is one of the challenges. If, for example, the part update from a CAD engineer does not include the pockets that are required in the assembly, to the CAM engineer.
SOLUTION: A modeler that enables developers of a CAM programs to create intuitive processes for features such as feature extraction and duplication across CAD version updates. A modeler is capable of recognizing and extracting the pocket's architecture and the parameters that define it. Additionally, the CAM application can enable the engineer to reproduce the pocket in a few simple steps by exploiting the modeler's editing features such as scaling, filling, extruding, symmetrical patterning, and removing.
Last Minute Design Updates
The second major challenge is last-minute design changes may impact manufacturers as a result of simulation.
SOLUTION: With 3D software components, you may create applications in which many simulation engineers can work together to make design modifications to the CAD at the same time, with the changes being automatically merged at the end.
Challenging Human-driven CAM Manufacturing
The third major challenge we have included is that CAM engineers must perform manual steps in human-driven CAM programming, which takes time and requires expert CAM software developers. Furthermore, when the structure of the target components grows more complicated, the associated costs and possibility of human failure rise.
SOLUTION: Self-driving CAM is the best solution for this challenge. Machine-driven CAM programming, also known as self-driving CAM, provides an opportunity to improve this approach with a more automated solution. Preparing for CAM is simple with the self-driving CAM approach, and it can be done by untrained operators regardless of part complexity. The technology handles all of the necessary decisions for CAM programming operations automatically. In conclusion, self-driving CAM allows for efficient fabrication of bespoke parts, which can provide substantial value and potential for job shops and machine tool builders.
Computer Aided Manufacturing Examples
CAM is widely utilized in various sectors and has emerged as a dominant technology in the manufacturing and design industries. Here are two examples of sectors where CAM is employed efficiently and drives solutions to many challenges in the specific business.
Virtual 3D prototype systems, such as Modaris 3D fit and Marvellous Designer, are already used by designers and manufacturers to visualize 2D blueprints into 3D virtual prototyping. Many other programs, such as Accumark V-stitcher and Optitex 3D runway, show the user a 3D simulation to show how a garment fits and how the cloth drapes to educate the customer better.
Aerospace and Astronomy
The James Webb Space Telescope's 18 hexagonal beryllium segments require the utmost level of precision, and CAM is providing it. Its primary mirror is 1.3 meters wide and 250 kilograms heavy, but machining and etching will reduce the weight by 92% to just 21 kilograms.
What is the best software for CAM?
Mastercam has been the most extensively utilized CAM software for 26 years in a row, according to CIMdata, an independent NC research business.
How CAD-CAM helps manufacturers?
Customers can send CAD files to manufacturers via CAD-CAM software. They can then build up the machining tool path and run simulations to calculate the machining cycle times.
What is the difference between CAD and CAM?
Computer-aided design (CAD) is the process of developing a design (drafting). CAM is the use of computers and software to guide machines to build something, usually a mass-produced part.
Article | May 10, 2021
Jason Spera, picture left, recently shared his vantage of the changes for factory floor automation in 2021. Jason is CEO and Co-Founder, Aegis Software. Spera is a leader in MES/MOM software platforms for discrete manufacturers with particular expertise in electronics manufacturing. Founded in 1997, today more than 2,200 factory sites worldwide use some form of Aegis software to improve productivity and quality while meeting regulatory, compliance and traceability challenges. Spera's background as a manufacturing engineer in an electronics manufacturing company and the needs he saw in that role led to the creation of the original software products and continue to inform the vision that drives Aegis solutions, like FactoryLogix. He regularly speaks on topics surrounding factory digitization, IIoT, and Industry 4.0. Contact Jason on LinkedIn.
Article | December 7, 2021
Machine learning in manufacturing is becoming more widespread, with businesses like GE, Siemens, Intel, Bosch, NVIDIA, and Microsoft all investing heavily in machine learning-based ways to enhance manufacturing.
Machine learning is predicted to expand from $1 billion in 2016 to USD 9 billion by 2022at a compound annual growth rate (CAGR) of 44% throughout the forecast period, according to Markets & Markets.
The technology is being utilized to cut labor costs, achieve better transition times, and increase manufacturing speed.
“I advocate business leaders get to know more about what AI can do and then leverage AI in proofs of concept.”
– Michael Walton, Director and Industry Executive, Microsoft speaking with Media 7
Machine learning can help enhance manufacturing processes at the industrial level. This can be achieved by assessing current manufacturing models and identifying flaws and pain factors. Businesses can rapidly address any difficulties to keep the manufacturing pipeline running smoothly.
Let us explore how machine learning is transforming manufacturing operations.
How Machine Learning Is Transforming Manufacturing Operations
“The greatest benefit of machine learning may ultimately be not what the machines learn but what we learn by teaching them.”
- Pedro Domingos
Machine learning in manufacturing is revolutionizing manufacturing operations and making them more advanced and result-oriented, so let's have a look at how this is unfolding.
Allows for Predictive Maintenance
Machine learning provides predictive maintenance by forecasting equipment breakdowns and eliminating wasteful downtime. Manufacturers spend far too much time correcting problems instead of planning upkeep. In addition to enhancing asset dependability and product quality, machine learning systems can forecast equipment breakdown with 92% accuracy. Machine learning and predictive analytics increased overall equipment efficiency from 65% to 85%.
Increases Product Inspection and Quality Control
Machine learning is also utilized for product inspection. Automated inspection and supervision using ML-based computer vision algorithms can discriminate between excellent and bad products. These algorithms simply need excellent samples to train; therefore a fault library is not required. However, an algorithm that compares samples to the most common errors can be built. Machine learning reduces visual quality control costs in manufacturing. Forbe's says AI-powered quality testing can boost detection rates by up to 80%.
Logistics-related Tasks Are Automated
To run a production line, industrial companies need considerable logistics skills. The use of machine learning-based solutions can improve logistics efficiency and save expenses. Manual, time-consuming operations like logistics and production-related documentation cost the average US business $171,340 annually. It saves thousands of manual working hours every year to automate these everyday procedures. Using Deep Mind AI, Google was able to lower its data center cooling bill by 40%.
Creates More Business Opportunities
Machine learning is frequently used in the production process. Substantial data analysis is required to create new items or improve existing products. Collection and analysis of huge amounts of product data can help find hidden defects and new business opportunities. This can help improve existing product designs and provide new revenue streams for the company. With machine learning, companies can reduce product development risks by making smarter decisions with better insights.
Protects Company’s Digital Assets
On-premise and cloud-based machine learning systems require networks, data, and technological platforms to function. Machine learning can help secure these systems and data by restricting access to vital digital platforms and information. Humans’ access sensitive data, choose applications, and connect to it using machine learning. This can help secure digital assets by immediately recognizing irregularities and taking appropriate action.
Harley Davidson's Sales Climbed by 40% Using Albert – The ML & AI-Powered Robot
Today, traditional marketing is harder to break through. It's easy to see why Albert (an AI-powered robot) would be a good fit for Harley Davidson NYC. Thanks to machine learning and artificial intelligence, robots are producing news stories, working in hotels, controlling traffic, and even running McDonald's.
Albert works well with social media and email marketing. It analyzed which customers are more likely to convert and modifies the personal creative copies on its own for the next process.
Harley-Davidson is the only company to employ Albert in its business. The company evaluated customer data to find prior consumers who made purchases and spent more time browsing the website than normal. Albert used this data to categorize customers and scale up test campaigns.
Using Albert, Harley-Davidson's sales climbed by 40% and leads increased 2,930%, with half coming from high-converting ‘lookalikes' detected by AI and machine learning.
The groundbreaking benefits of machine learning are the pillars of machine learning applications in manufacturing. Machine learning in manufacturing helps enhance productivity without compromising quality. According to Forbes, Amazon has automated warehouse logistics picking and packing using a machine learning system. With Kiva's help, Amazon's typical ‘click to ship' time dropped from 60-75 minutes to 15 minutes. So, industry leaders are seeing fantastic outcomes, and machine learning in manufacturing is the future.
How is machine learning used in manufacturing?
Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process.
Which two forms of machine learning are there?
Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data.
What is a machine learning model?
A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm.
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"name": "Which two forms of machine learning are there?",
"text": "Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data."
"name": "What is a machine learning model?",
"text": "A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm."
Article | December 8, 2021
Why should warehouses be left behind as everything gets smarter in the manufacturing world? The future warehouse will be smarter and more innovative to speed up supply chain management procedures and assist businesses in intelligently segregating their raw materials and manufactured goods.
So, what does it mean to have "a smart warehouse"?
A smart warehouse is a big infrastructure that stores raw materials and manufactured goods and employs machines and computers to handle routine warehouse tasks that humans previously performed. Smart warehouses are inspired by smart factories and operate in a data-driven environment. It is the ability of the system in the warehouse to make it more efficient and productive by utilizing networked, automated technology.
“I advocate business leaders get to know more about what AI can do and then leverage AI in proofs of concept.”
– Michael Walton, Director, Industry Executive (Manufacturing) at Microsoft
According to EASYECOM, nine out of ten businesses intend to include commercial service robots into their operations in some form. By 2025, it is projected that there will be roughly 23,000 robotic warehouses in the United States alone, up from only 2,500 in 2018.
Furthermore, the global smart warehousing market is expected to grow at a CAGR of 11.5 percent from USD 14.8 billion in 2021 to USD 25.4 billion in 2026, according to GlobeNewswire. As can be seen, the current warehouse automation trends are scaling up the worldwide market for smart warehouses, and the value of the smart warehouse business has a long way to go in the future.
So, what are the technologies that are changing traditional warehouses into intelligent warehouses? Continue reading this article to get a better understanding of this.
Top 5 Warehouse Technologies to Take On
Numerous manufacturing and non-manufacturing organizations, including IKEA, NIKE, and WALMART, utilize smart warehouses to streamline their overall operations. The technologies listed below assist many of them in implementing the modern warehousing idea.
A Warehouse Management System
Warehouse Management Systems, or WMSs, are comprehensive software systems that consolidate all of your critical data onto a single platform that can be easily accessed by team members and selected supply chain partners. This data compartmentalization allows for lightning-fast reporting, which allows for super-efficient planning, even for unexpected events. Overall, the use of warehouse management systems complements the use of other automated aspects perfectly.
Automated Picking Tools
The days of error-prone picking are long gone; now, when picking automation elements are integrated into the flow, warehouses can profit from near-perfect picking rates. In addition, picking procedures can be aided by various techniques, including voice-automated order picking, pick-to-light, and robotic order picking. These technologies also use cutting-edge barcoding choices that easily interface with your selected management software to provide the quickest and most accurate automated reporting experiences.
Automated Guided Vehicles (AGVs)
AGVs, or automatic guided vehicles, are the best approach to speeding up storage and retrieval processes. AGVs are becoming more robust as technology advances, but older models have proven safer and more cost-effective than manual labor. Their functions include pallet, rack, and other container storage and controlling and automating the entire receiving process.
Platforms for Automated Inventory Control
Automated inventory control platforms, when combined with a few other technological cornerstones, such as asset and inventory tags, may eliminate labor, guesswork, and unnecessary time from traditional inventory control. In addition, there are several advantages to using these platforms, including their ability to automatically count inventories and synthesize data for real-time reporting that can be viewed remotely.
The Internet of Things (IoT) is used by some of the world's most efficient smart warehouses, such as Amazon, as an entire concept rather than a specific technology. All of your automated and manual operations may be optimized when IoT is used to control all of your moving parts, both automated and manual. This innovative technology helps optimize a warehouse's inventory control systems, workforce planning, and, of course, the overall customer experience.
While implementing technology improves the notion of a smart warehouse, it isn't always possible for every warehouse to do so instantly, especially since implementing technology takes significant financial and infrastructure changes. That's why warehouses are adopting the concept of collaborative robots (cobots). These are the autonomous elements that work with existing human workers. Cobots allow warehouses to preserve many of their existing procedures and infrastructure while gaining the benefits of fully autonomous elements.
Amazon's Smart Warehouses Integrates Humans and Robots
Amazon acquired Kiva Systems for $775 million in 2012, highlighting its interest in warehouse robotics. Kiva Systems was the sole known producer of warehouse robots, serving many different logistics organizations.
Amazon bought Kiva Systems' machines, constructed and used them all. Amazon Robotics is a new business unit that the company has developed.
Amazon recently established a semi-automated warehouse with human workers and robots. As a result, simple chores like moving parcels and scanning barcodes are automated. However, organizing goods and carrying complex objects (like bottles) is still part of human work.
Amazon's automated warehouse employs over 400 robots and hundreds of human employees.
Amazon's rise in two crucial areas – online shopping and logistics – has been accelerated by warehouse robots.
Modern warehousing is a new trend in the manufacturing industry that automates numerous procedures required for keeping manufacturing materials and products organized. Technology trends in warehousing are making manufacturers' jobs easier and promoting the future warehouse model in 2022. Implement the cutting-edge technology outlined above to stay current with warehousing trends and boost productivity, efficiency, accuracy, and flexibility for your personnel and their operations.
What are the key benefits of a smart warehouse?
A smart warehouse improves the warehouse's productivity, efficiency, and accuracy. It also allows personnel and procedures to be flexible.
What exactly is WMS?
A warehouse management system (WMS) is a software solution that handles the supply chain from the distribution center to the retail shelf.
What is COBOT?
Cobots are designed to work with people rather than replace them. Cobots are also known as people-focused robots. They can help humans simplify and improve their work.
"name": "What are the key benefits of a smart warehouse?",
"text": "A smart warehouse improves the warehouse's productivity, efficiency, and accuracy. It also allows personnel and procedures to be flexible."
"name": "What exactly is WMS?",
"text": "A warehouse management system (WMS) is a software solution that handles the supply chain from the distribution center to the retail shelf."
"name": "What is COBOT?",
"text": "Cobots are designed to work with people rather than replace them. Cobots are also known as people-focused robots. They can help humans simplify and improve their work."