Industry 4.0, also known as smart manufacturing, has been well underway for some time now, and more manufacturers are undergoing digital transformations as the benefits become more apparent. Smart manufacturing technologies are also becoming more accessible — in March of this year, the Biden-Harris Administration announced $50 million in funding to ensure the removal of existing barriers that prevent the usage of data-driven technologies by small and medium-sized manufacturers.
The rising prevalence of smart manufacturing is undeniable, but what many manufacturers might not be prepared for are the potential roadblocks that can come up when starting out on a digital transformation journey.
When it comes to setting up a successful smart factory, preparation and awareness are key. Read on for the big mistakes manufacturers should look to avoid when setting up a smart factory.
Data is a fundamental component of a smart factory — but not just any data. It must be data that is properly organized, visualized, and contextualized to extract the highest value possible.
Data collection in a smart factory is made possible often through devices and machinery equipped with Industrial Internet of Things (IIoT) sensors capable of monitoring manufacturing variables and processes. At the beginning stages of setting up a smart factory, manufacturers may experience overwhelm at the flood of data coming in from various sensors all across their operations. This is especially true when analysis is being performed manually or at a basic level — the last thing any manufacturer wants is to allot valuable time and resources to data management and analysis, only to end up with insufficient or incomplete insights.
For a smart factory to ultimately be successful, it is crucial that data is leveraged to its fullest extent. In order for this to be so, manufacturers must ensure their smart factory is being driven by advanced artificial intelligence (AI) and machine learning (ML), key smart manufacturing technologies capable of extracting actionable intelligence from data, in real time, that can power better decision making. Not only will this aid in executing better solutions to issues, it can even prevent problems before they occur, along with revealing important opportunities for improvement.
Mistake #2: A Lack Of A Unified Approach
A true smart factory is not bound inside the four walls of one facility. Rather, it operates in conjunction with supply chain operations and the broader manufacturing business network. Connectivity is key for creating a more optimized, successful smart manufacturing enterprise.
A lack of a unified approach from the outset can prevent manufacturers from getting the most out of their smart factory. Fragmented systems make communication and collaboration difficult. Blind spots and inefficiencies can accumulate and become costly, quickly.
To avoid this, manufacturers must implement solutions that facilitate visibility and data sharing across multiple partners and suppliers within the enterprise. Incorporating the use of a cloud-based platform can provide a single source of truth for cross-supply chain decision-making, increasing end-to-end visibility and traceability, while extending connectivity, communication, and collaboration across the organization.
Mistake #3: Trying To Do Everything All At Once
Setting up a smart factory is an evolving process, rather than a swiftly-achieved outcome. The pathway to a successful smart factory is one that is taken with measured consideration and intentional strategy.
A common mistake manufacturers make when setting up their smart factory is doing too much, too soon. A digital transformation does not necessitate an instantaneous overhaul — assuming so would mean facing an impractical, impossible task involving counter-productive complexities and a time-consuming period of shutdown.
Dividing the process into manageable steps is the best approach when making the transition to a smart factory. At each stage, manufacturers can review their progress in order that they may visualize precisely how newly introduced technologies are adding value to their operations. This measured approach also gives employees the time needed to adjust to a new working environment, while giving business leaders ample time to make informed decisions before scaling.
Setting up a smart factory may seem like a daunting endeavor, but it needn’t be. By understanding some of the potential traps involved like the ones above, manufacturers can instead take a strategic approach, ensuring their investment pays off while discovering the full range of benefits smart manufacturing can provide.
A Clear Path To Industry 4.0 Smart Manufacturing
With the right manufacturing platform, manufacturers have the guesswork taken out of the equation when it comes to setting up a smart factory.
ThinkIQ, the leader in Transformational Intelligence for manufacturers, illuminates a clear path to digital transformation through the 5 steps required to reach Industry 4.0 Smart Manufacturing status: Data Capture, Visualization & Integration, Material-Centric Insight, and Transformational Intelligence, all leading to fully autonomous Smart Manufacturing.
With ThinkIQ’s Transformational Intelligence platform, you’ll finally have a complete overview of all manufacturing operations. Changes in any variable are intelligently linked to both actual and predictive outcomes. Data is contextualized both in-plant and across your supply chain to deliver Smart Manufacturing that improves yield, safety, quality, and compliance. Simply put, actionable end-to-end data insights lead to safer, better quality products and improved key metrics.
At ThinkIQ, we don’t just gather data. We don’t just analyze data. We make sense of the data, and suggest actions that enhance safety, reliability, and efficiency.
Set up your business for Smart Manufacturing success — Contact a ThinkIQ expert today to start your digital transformation journey. You can also download our new eBook,”The Smart Factory’s Goal of End-to-End Supply Chain Visibility,” to learn more about how ThinkIQ’s computer vision and continuous intelligence solutions can help illuminate critical blind spots across the supply chain.