I am the Managing Director of Arvense Group, a firm that helps engineering and manufacturing companies become more competitive.
The motivation for companies to implement Industry 4.0 projects varies from increasing productivity to alleviating the impact of labor shortages, but the fact is that these projects require significant changes to the factory floor that are often not considered. While IoT-enabled equipment and advanced real-time data analysis take most of the limelight in Industry 4.0 discussions, successful implementation of these processes requires a holistic approach with an eye to the entire operation to fully realize the benefits.
We often see companies that have ventured into the smart manufacturing space being stuck in so-called pilot purgatory where they have one state-of-the-art, flagship facility but fail to horizontally deploy the advancements to their other facilities. One of the reasons for this failure is the realization of how radically they would need to change the shop floor to accommodate the advancements of the pilot facility. This has led to a belief that smart manufacturing is only feasible for new facilities.
Instead of looking at Industry 4.0 as a capital-intensive flagship project, it needs to be viewed as a tool that can be used to lay a strong foundation for future manufacturing advancements. Below are five ways in which Industry 4.0 can transform and advance the factory floor:
Drive Increased Modularity In Products And Subsequently Their Manufacturing Cells
One of the biggest drivers of smart manufacturing is expanding the use of automation. To achieve this, product designs need to be optimized for automated assembly and manufacturability. This involves designing out components like flexible piping, extensive wiring harnesses and fasteners — which are a hindrance to automated assembly — and incorporating modules with position locators that robots can easily assemble.
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ByAmy DaniseEditorThe material flow requirements of a fully automated assembly cell are different from that of an operator-based assembly cell. Due to this, a fundamental redesign of the manufacturing cells is needed to accommodate increased automation.
Consolidation Of Previously Distinct Processes
In the past, processes may have been kept distinct due to the differences in line speed. This required storage space for semi-finished inventory on the shop floor. Smart manufacturing can help create a seamless manufacturing process enabling one-piece flow through the factory. This will reduce the need for previously distinct processes, enabling optimum line balancing. Make sure to use this freed-up and valuable floor space for future capacity improvements.
Increased Functionality From A Given Asset
The advantages of gathering data from an asset to help drive business and operations decisions are well known. But where Industry 4.0 truly stands out is by incorporating machine learning and artificial intelligence (AI) into those assets to help automate some of the process controls and troubleshoot decisions.
The ongoing labor shortage has also impacted the maintenance department size in manufacturing facilities. You can use machine learning to help automate equipment troubleshooting and reduce the downtime impact. Data analytics also enables effective, predictive maintenance which can optimize the allocation of limited maintenance personnel.
Connected Technology Stack
The challenge of organizational silos is often intensified by fragmented and disconnected software systems. This creates waste through lack of data, incorrect data or missed communications that cause misalignments across the organization.
Connecting systems through a single digital thread enables engineering to communicate changes simultaneously with manufacturing, supply chain and logistics. This is one example where communication gaps and wasted time can be reduced. One note of caution, when the software systems are connected, the updates can be cascaded in real time. This will have a significant impact. To accommodate this risk, appropriate system approvals must be in place to ensure accuracy prior to implementing changes across the enterprise.
Reduce The Time Frames Of Lean Six Sigma Projects
Lean manufacturing projects are critical to achieving continuous improvement of the manufacturing process, but one of the most time-consuming aspects of these projects is the collection of data and its analysis. Data analytics and AI, by their very nature, significantly reduce the time required to collect and analyze the data, enabling employees to allocate more time toward developing innovative improvements and implementing them faster.
Having a virtual twin of the facility also helps validate the proposed solution by simulating the impact and ROI for the project, resulting in increased confidence from all levels within the company prior to significant investment in capital and personnel.
Industry 4.0 is all about enabling the companies to not only address current pain points but also build a stronger future-ready foundation for continuous and sustainable growth. Leaders that give the points above thorough consideration should increase the probability of maximizing their transformation efforts to their full potential.
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