Manufacturing has undergone a digital transformation. The traditional factory floor has evolved into an interconnected, data-driven environment known as smart manufacturing – an approach that aims to improve manufacturing and production processes.
Smart manufacturing adoption grew by 50% last year,1 and it's not hard to see why. Organizations that implement manufacturing IT solutions can optimize their operations, maximize efficiency, reduce costs, and much more.
If you haven't embraced smart manufacturing yet, it's time to get on board. In this blog, we'll explain what smart manufacturing is, how it helps manufacturers solve challenges, and how you can start leveraging it today to modernize your business.
Optimizing your operations to reduce downtime, improve your bottom line, and support the supply chain requires taking a proactive approach to your IT – which isn't always easy to come by in the Midwest.
Manufacturing businesses in Milwaukee and Chicagoland often struggle to:
Adopting smart manufacturing technologies can help you overcome these challenges and keep your operations running smoothly.
Smart manufacturing is the use of advanced technologies to create an automated manufacturing process. It leverages Internet of Things sensors, big data analytics, artificial intelligence, robotics, and machine learning to monitor and control manufacturing systems in real-time.
With smart manufacturing, businesses can increase efficiency, improve product quality, save money, and more. It signifies a transformative shift from traditional manufacturing processes towards a more digitized and networked production model.
Some characteristics of smart manufacturing include:
In a smart factory, all devices, systems, and machines are networked together and can communicate critical data via sensors. This connectivity allows for increased visibility across operations.
Advanced robotics and AI take over dangerous, repetitive, and routine manufacturing tasks, freeing up the human workforce for higher-value work and improving safety.
Smart manufacturing solutions collect, aggregate, analyze, and turn the vast amounts of operational data created during operations into real-time insights that drive decision-making.
Thanks to the abundance of data and flexibility of smart manufacturing machines, production lines can quickly adapt to accommodate changing customer demands and market trends.
By combining data patterns with machine learning, smart manufacturing solutions enable manufacturers to predict potential equipment failures, quality issues, output gaps, and more before they occur.
The original Industrial Revolution began around the mid 1700s, and manufacturing systems have gotten faster, stronger, and more efficient ever since.
While the First Industrial Revolution was defined by steam power, the Second Industrial Revolution introduced the assembly line and mass production processes. Data-enhanced automation was developed during the Third Industrial Revolution, and the latest iteration – the Fourth Industrial Revolution – is where we are today.
The term "smart manufacturing" came into widespread use when GE coined the phrase "Industrial Internet" to describe adding sensors, software, and big data processing capabilities to manufacturing operations. Over the next few years, developments in industrial Internet of Things (IIoT), AI, and cloud computing drove further advances in internet-connected machinery and the smart manufacturing ecosystem.
Smart manufacturing leverages advanced technologies to create an efficient, interconnected production system. Some of the key technologies enabling the smart manufacturing process are:
IIoT devices are at the heart of digital manufacturing. They include industrial devices and sensors used to collect data from internet-connected machinery, which helps improve manufacturing performance, reduce downtime, and more.
As manufacturing data grows, more organizations are turning to artificial intelligence to supplement human analysis. Around 74% of manufacturers currently use or plan to use AI,1 which can analyze generated data to uncover inefficiencies, predict issues, and make data-driven decisions.
Digital twins are virtual representations of products or systems. Manufacturers use digital twins to simulate the production process in a virtual environment, allowing them to test and optimize processes before implementing them in the real world.
Advanced robots powered by AI and sophisticated sensing technologies can take over repetitive and labor-intensive tasks with precision and consistency. These machines function alongside operators to improve worker safety and reduce human error.
94% of manufacturers use data analytics and visualization to streamline the supply network.2 Predictive analytics take a technology-driven approach to drawing insights from manufacturing data through predictive modeling, machine learning, and digital twin modeling.
Cloud platforms offer centralized access to manufacturing data across multiple locations – while also providing the immense computing power needed for big data analytics. Edge computing brings processing power closer to data sources, reducing latency and delivering real-time decision-making at the production site.
Also known as 3D printing, additive manufacturing enables cost-effective, on-demand production of highly customizable final parts and products. It reduces waste and the need for spare part inventories.
Cyber attacks targeting manufacturing companies accounted for nearly 25% of the total attacks in 2022.3 With so much interconnected technology at stake, cyber security solutions like network encryption, access controls, malware protection, and multi-factor authentication are essential for securing your data network.
Smart factories that provide supply chain management are exploring blockchain technology for its transparency, traceability, and security as a fast and efficient way to record and store manufacturing data.
Augmented and virtual reality can provide immersive, flexible technical workforce training simulations while assisting human workers on the factory floor through hands-free instructions and information.
Like any transformative technology, smart manufacturing comes with its own set of advantages and challenges. Read on to explore the pros and cons of the smart manufacturing movement.
Smart manufacturing has gained momentum over the past few years, but how exactly does it differ from its conventional counterpart? Here are some of the biggest differences between smart manufacturing and traditional manufacturing processes:
Where traditional manufacturing is heavily dependent on human labor, smart manufacturing takes a technology-driven approach to production by leveraging automation tools like robotics, IoT, and artificial intelligence.
Traditional supply chains were linear, with limited visibility and coordination. Smart factories are integrated across departments and partners for transparency and responsiveness across the supply chain.
In traditional production processes, collected data was minimal and siloed. Smart manufacturing applies sensors and internet-connected systems across the factory to collect and analyze data for real-time insights.
Traditional systems relied on manual adjustments to adapt to changes, which was slow and inefficient. Smart factory systems use real-time data and industrial connectivity devices to automatically adapt production.
Decisions in conventional manufacturing were made by managers in a centralized, top-down approach. Smart manufacturing enables decentralized, localized decision-making using analytics at an edge device level.
Traditional systems relied on assembly lines with limited flexibility. Smart manufacturing uses a modular design for rapid prototyping, which makes it easy to produce customized or small-batch products.
In traditional factories, communication between different manufacturing machines can be limited or nonexistent. Smart manufacturing thrives on connectivity, enabling seamless data sharing, coordination, and communication between various parts of the production process.
Traditional manufacturing relies on a skilled workforce, but employees often lack specialization in areas like data analytics and digital technology. With smart manufacturing, teams must be able to operate, maintain, and troubleshoot systems effectively, which may require upskilling and training programs.
In traditional manufacturing, maintenance was routine-based. Smart manufacturing uses predictive maintenance analytics to assess equipment performance and predict maintenance needs ahead of time.
Smart manufacturing can transform your production into an intelligent, interconnected ecosystem – but selecting the right technologies is key to getting the most value for your efforts.
Andromeda has helped businesses in the manufacturing industry implement best-fit technology solutions for over 27 years. We know having the wrong technology in place or relying on outdated systems can leave manufacturers in the Midwest struggling to stay competitive, which is why we take a proactive – not reactive – approach to modernizing your operations.
Ready to start your smart manufacturing journey? Book a meeting with our network infrastructure experts today.
Sources: