The transformation of digital manufacturing technology is not something far off. Industry 4.0 technologies are actively being used today to optimize manufacturing operations with connected capabilities. Once active, digital tools enable manufacturers to optimize efficiency, break down data silos into actionable insights, produce more accurate demand forecasting and predictive maintenance schedules, all while promoting safety on the factory floor.
The connected capabilities of a digital factory present a number of opportunities for manufacturers to gain scalable agility, flexibility and operational performance. Digital manufacturing converges IT (informational Technology) and OT (Operational Technology), creating a manufacturing process that is empowered by cyber-physical capabilities. These digital tools helps to bridge the gap between isolated processes to provide operational transparency at a glance.
IIoT broadly refers to a series of internet connected sensors and devices that provide real-time data from across the factory floor, allowing for improved visibility for machine performance. Similarly, this technology also has profound implications for supply chain logistics, promising to eliminate wasted time and energy associated with inventory oversights. IoT sensors can be deployed for virtually anything including factory floor machinery, lights, HVAC (Heating, ventilation, air-conditioning), biometric locks, and more. For instance, IIoT allowed global tech firm, CGI to use connected sensors in elevators that in turn provide real-time data that is used to create predictive maintenance schedules.
The increased number of connected devices in a manufacturing setting produces massive amounts of data. Data analytics tools like artificial intelligence and machine learning help translate big data into actionable insights that are then used to project demand forecasting and predictive maintenance schedules. This process serves to discover and eliminate areas of waste and break down data silos, serving to increase efficiency and transparency across the manufacturing process.
Cloud services work as the backbone of many of these technologies, allowing for over the air transfer of real time data. Rather than trying to rapidly acquire server storage, cloud allows manufactures to securely retrieve and store the massive amounts of information generated from the factory floor. Cloud creates easy solutions for computationally intensive tasks like risk modelling that informs machine learning, ultimately serving to reduce costs on high-powered machinery. These tools also allow for mobility, collecting and analyzing data from across production sites in real time to create a real-time overview of daily performance. Further, access programs can utilized from any computer in the organization creating centralized management that is freed from the control room.
Robotics are a staple of manufacturing environments serving to automate repetitive tasks and heighten efficiency while promoting worker safety. However, advancements in robots allow for the automation of increasingly sophisticated tasks. Modern examples include machine arms that can manipulated by a human operator in a 3D space to simulate specific motions. The Machine can then automate those same motions while evaluating and optimizing its own performance. Likewise, autonomous robot vehicles can create more efficient packing protocols in the warehouse by quickly analyzing tasks and choosing the most efficient route to retrieve items, even when accounting for multiple orders.
In factory settings, 3D printing, also known as additive manufacturing, allows for specialized production of unique or customized products and components. When working in concert with predictive maintenance schedules, additive manufacturing can produce replacement components in one print well before repair or replacement becomes a critical concern. Similarly, mainstream adopters like Nike connect consumers to the production line by giving them web tools to customize shoe design that are then 3D printed. These are just a few of the applications, but this technology has implications for the entire production process, allowing for the printing single items rather than assembly from other components.
The digital thread is a 3D models of physical assets, operational systems and structures throughout the factory space. This virtual representation used in conjunction with IIoT sensors gives manufacturers a view the entirety of the entire factory floor in a virtual space, showing asset locations, machine uptime, and maintenance needs, even providing a view from the inside of a machines. These 3D models are then used to create a digital twin that can simulate stress testing, promote rapid prototyping, and train employees before introducing them to the physical machines on the floor.
Using display tools such as internet connected glasses or a tablet, augmented reality can transform the manufacturing experience by providing asset status, performance or task specific information at a glance. This enhances cyber-physical capabilities by creating a real time view maintenance concerns and analytics informed while operators are present on the factory floor. This technology can also serve to train new employees by showing safety protocols for each machine and how that relates to their specific duties. Likewise, AR devices can show precise locations, components and protocols for maintenance.
Developing digital manufacturing capabilities requires a careful examination of the existing components and features that make a production line successful.
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