While integration between legacy systems and connected technologies remains challenging, the benefits of building a digital factory are certain to boost advanced manufacturing capabilities.
As the convergence of digital technologies continue to drive the 4th industrial revolution, manufacturers find themselves in a race to acquire new capabilities made possible through digital technologies.
Despite this reality, according to a recent Forrester Report, while more than 90% of manufacturing decision-makers believe that digital transformation is important to their organization’s success, only 12% say that they have delivered digital transformation programs across their business.
With so much room for growth, the challenges of integrating legacy systems become hard pain points for manufacturers looking to keep pace with competitors making similar advancements. While digital factories enable manufactures to flexibly scale in today’s disruptive landscape, it remains imperative to recognize how poorly implemented Industry 4.0 solutions can hinder the very advancements they aim to provide.
Read on to learn how the successful implementation of the digital factory can transform advanced manufacturing.
A digital factory is made possible by advancements in information technologies that enable manufacturers to virtualize their existing systems. While some of these Industry 4.0 or smart manufacturing technologies are now over 10 years old, the convergence of innovations such as artificial intelligence, big data, automation, Industrial Internet-of-Things (IIoT), robotics, additive manufacturing (or 3D printing), and augmented reality present the opportunity to accelerate production capabilities while reducing waste.
However, these solutions are not one-size-fits-all. Successfully building a digital factory requires customized implementation that addresses the scope of a business’s needs. Achieving the desired transformation is not the result a single sudden change but is instead achieved through agile sprints where new technology is implemented and evaluated against long term goals.
Poor integration between legacy systems and digital technologies can lead to slow downs, and this challenge is likely why the current percentage of manufacturers operating with digital factories remains small.
Once operational, however, digital or smart factories are noted for improved safety conditions on the factory floor, automated systems, analytics guided predictive maintenance schedules, more efficient management of raw materials and reduced waste across the supply network, and sophisticated development strategies that accelerate time to market.
While the specifics of virtualizing production processes are necessarily tied to each manufacturer’s unique circumstance, there are several strategies that remain vital to the successful implementation of a digital factory:
The Industrial Internet of things (IIoT) allows for a wide scale of sensors and connected technologies to actively track and share data with decentralized control centers. Recognizing that each production process is unique, it is vital to discover what key data points drive optimization. The development of cyber-physical systems (CPS) integrates the dynamics of physical processes with software, creating new possibilities for communication, modeling, design, and analysis strategies.
In moving information systems to the cloud, existing data silos are transformed into active sources for data analytics, which contribute to real time factory floor updates. Additionally, edge computing interprets information at the location it is collected, providing insights in place of raw data. Moving legacy systems to cloud services can be a daunting task, but promises to create a more agile operation that can detect problems before they arise.
Once cloud and IIoT systems are in place, the next transformation is one of company culture. With the use of AI assisted machine learning, a digital factory can automate production processes. This is often feared as process that threatens to eliminate jobs, while it is true that automation can reduce the number of operators on the factory floor, it also heightens the demand for operators who accurately read and act insights driven by data analytics. Equipping employees with the education and tools needed to interpret and act on analyzed data remains paramount.
The digital factory begins with the creation of a digital thread, the lowest level design and specification for a digital representation of a physical item, critical to model-based systems engineering (MBSE). Through 3D modeling, a manufacturer can create virtual representations of all the assets present on the factory floor, creating a digital twin. This allows managers to configure, model, simulate, assess and evaluate items, procedures and systems before the factory is constructed.
The digital twin depends on those baselines set by the “thread” to maintain accuracy in simulation and to drive machine learning. At its best, manufacturers can use their digital twin to accelerate development by testing new product designs against their factory’s current operational capabilities, saving both time and resources while accelerating time to market.
Advancements in information technology can transform the factory floor without necessarily replacing major features of the production system. AI and cloud computing holistically review existing manufacturing systems from end-to-end, working the big data generated by factory floor conditions to present real time data analytics.
These data driven insights allow manufacturers to track weaknesses in the supply network, reducing waste while ensuring that raw materials are being used efficiently. While still in its infancy, industrial augmented reality will soon allow operators to track data analytics and insights at glace while navigating the factory floor.
Automation has been standard feature of manufacturing systems since the 1970’s, both to optimize routine or mundane tasks and to improve worker safety. In the digital factory, however, interconnected connected systems present new opportunities. Advancements in robotics enable manufacturers to automate increasingly more sophisticated tasks.
In some instances, manufacturers have been able to automate the production of replacement components through additive manufacturing. When conditions are met and AI determines that predictive maintenance is necessary, the right system can automatically 3D print necessary components so that they can be replaced as soon as operators are available.
While the construction of a digital factory presents a variety of challenges, achieve the capabilities of advanced manufacturing are worth the risk. Stefanini stands at the forefront of digital technology. Our team of experts are uniquely positioned to assist manufacturers in implementing digital transformation.
We take a customer-first approach to everything we do, analyzing your pain points and business objectives to co-create a solution custom fit for you. Ready to bring your factory into the future? Give us a call today!
Ready to bring your factory into the future? Give us a call today!
See what's trending
Hi. Need help?