Article | January 20, 2022
A smart factory that leverages Industry 4.0 concepts to elevate its operations has long been a model for other industries that are still figuring out how to travel the digital manufacturing route. Smart manufacturing technology is all you need to know if you're looking to cash in on this trend.
“Industry 4.0 is not really a revolution. It’s more of an evolution.”
– Christian Kubis
In this article, we'll look at the advantages that many smart factory pioneers are getting from their smart factories. In addition, we will look at the top smart factory examples and understand how they applied the Industry 4.0 idea and excelled in their smart manufacturing adoption.
Industry 4.0 Technology Benefits
Manufacturing Industry 4.0 has several benefits that can alter the operations of manufacturers. Beyond optimization and automation, smart manufacturing Industry 4.0 aims to uncover new business prospects and models by increasing the efficiency, speed, and customer focus of manufacturing and associated industries.
Key benefits of Manufacturing Industry 4.0 in production include:
Improved productivity and efficiency
Increased collaboration and knowledge sharing
Better agility and adaptability
Improved customer experience
Reduced costs and increased profitability
Creates opportunities for innovation
World Smart Factory Case Studies and Lessons to Be Learned
Schneider Electric, France SAS
Schneider Electric's le Vaudreuil plant is a prime example of a smart factory Industry 4.0, having been regarded as one of the most modern manufacturing facilities in the world, utilizing Fourth Industrial Revolution technologies on a large scale. The factory has included cutting-edge digital technology, such as the EcoStruxureTM Augmented Operator Advisor, which enables operators to use augmented reality to accelerate operation and maintenance, resulting in a 2–7% increase in productivity. EcoStruxureTM Resource Advisor's initial deployment saves up to 30% on energy and contributes to long-term improvement.
Johnson & Johnson DePuy Synthes, Ireland
DePuy Synthes' medical device manufacturing plant, which started in 1997, just underwent a multimillion-dollar makeover to better integrate digitalization and Industry 4.0 smart manufacturing. Johnson & Johnson made a big investment in the Internet of Things. By linking equipment, the factory used IoT technology to create digital representations of physical assets (referred to as “digital twins”). These digital twins resulted in sophisticated machine insights. As a result of these insights, the company was able to reduce operating expenditures while simultaneously reducing machine downtime.
Bosch's Wuxi factory's digital transformation uses IIoT and big data. The company integrates its systems to keep track of the whole production process at its facilities. Embedding sensors in production machinery collects data on machine status and cycle time. When data is collected, complicated data analytics tools analyze it in real-time and alert workers to production bottlenecks. This strategy helps forecast equipment failures and allows the organization to arrange maintenance ahead of time. As a consequence, the manufacturer's equipment may run for longer.
The Tesla Gigafactory, Germany
According to Tesla, the Berlin Gigafactory is the world's most advanced high-volume electric vehicle production plant. On a 300-hectare facility in Grünheide, it produces batteries, powertrains, and cars, starting with the Model Y and Model 3. For Tesla, the goal is not merely to make a smart car, but also to construct a smart factory. The plant's photographs reveal an Industry 4.0 smart factory with solar panels on the roof, resulting in a more sustainable production method. On its official website, Tesla claimed to use cutting-edge casting methods and a highly efficient body shop to improve car safety. Tesla's relentless pursuit of manufacturing efficiency has allowed them to revolutionize the car industry.
The SmartFactoryKL was established to pave the way for the future's "intelligent factory." It is the world's first manufacturer-independent Industry 4.0 production facility, demonstrating the value of high-quality, flexible manufacturing and the effectiveness with which it can be deployed. The last four years, SmartFactoryKL has been guided by particular strategic objectives that drive innovation; the aim is to see artificial intelligence integrated into production. Two instances of AI-driven transformations include an "order-to-make' mass customization platform and a remote AI-enabled, intelligent service cloud platform that anticipates maintenance needs before they occur.
Enabling smart manufacturing means using the latest technology to improve processes and products. The aforementioned smart factory examples are industry leaders and are thriving by implementing Industry 4.0 technology. Small and medium-sized enterprises (SMEs) may use these smart factory examples to learn about the adoption process, challenges, and solutions. Industry 4.0 is aimed at improving enterprises and minimizing human effort in general. So adopt the smart factory concept and be productive.
What is the difference between a smart factory and a digital factory?
The digital factory enables the planning of factories using virtual reality and models, whereas the smart factory enables the operation and optimization of factories in real time.
Where does Industry 4.0 come from?
The term "Industry 4.0" was coined in Germany to represent data-driven, AI-powered, networked "smart factories" as the fourth industrial revolution's forerunner.
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 | November 23, 2021
Having recently returned from Uganda, had the pleasure of being introduced by Bernard Munyanziza of Nziza Hospitality to Gilbert Atuhire. He is the Managing Director at Value Addition Microfinance Ltd. which provides micro loans to producers and manufacturers.
Atuhire is an attorney by training, however his ability to articulate the core values of Lean Six Sigma and continuous process improvement were abundantly clear. The Kampala, Uganda offices are located on Parliamentary Avenue and Dewinton Rise. This central location allows direct access to industrial projects.
Article | July 13, 2021
The start of the new year is a great time to critically take a look at your processes and see how you can improve. Here at FANUC, we have identified four key strategies manufacturers can use to boost their efficiency!
Automation can increase production and efficiency no matter the type or complexity of the manufactured products. With space at a premium in most production facilities, many job shops look for machine tending robots that are easy to integrate and have a small footprint. FANUC's robots and software make it easy to connect the equipment and improve throughput as well as overall equipment effectiveness. Quick and Simple Startup of Robotization (QSSR) allows up to four machine tools to be connected with a robot using just one Ethernet cable.
Use the Latest and Greatest Machining Practices and Technology
Many manufacturers leave performance on the table due to outdated processes and programming. Are you getting the most out of your machining? Now’s the time to look at the advantages in new CNC technology. Because new controls have greater processing speed and can implement advanced algorithms, they can do a lot more for your operations. Moreover, the interfaces have become simpler and more intuitive, so they are easier to use than ever before.
Digitize Your Process
New digital tools are breathing innovation and life into increasingly more areas of manufacturing, including the application of digital twins in the machining industry. Digital twins provide virtualization of the machine, control and manufacturing process. Digitalizing traditional manufacturing processes have the potential to make operations more efficient by proving out production processes in the virtual world. That means less waste, more efficiency and a more equipped workforce.
Upgrade Your Shop with a CNC Retrofit
Do you have legacy equipment? Running older machinery can have hidden costs, such as taking the time to source and find older replacement controls leading to significantly longer total downtime and production losses. However, scrapping old equipment and starting new, might be too expensive, especially when factoring in tooling, fixturing, rigging and foundation. Plus, new machines may require more training for staff. A CNC retrofit, with new FANUC CNCs, industrial PCs, servos and cabling, can speed up processing and reduce cycle time by as much as 50 percent.