In today’s digital era, medical device manufacturers mostly rely on paper-based operations and systems that are long past their shelf life. Increasing production requirements are posing difficulties for manufacturers, because most processes are manual and the systems function in silos. Workers today don’t have quick access to the right information to perform their jobs. This significantly increases compliance and quality risks in the shop floor.
There is a growing need for centralised systems that can track and distribute content, and mobile applications that offer easy access to manufacturing processes. As a result, companies are integrating advanced mobile applications and cloud solutions that bring shop floors online. According to IDC, 77 per cent of manufacturers view digital transformation as an opportunity, while only 23 per cent see it as a risk, making digital transformation a top priority among most manufacturers. Sensing this trend, organisations are now digitising their shop floor, warehouses and supply chain network to improve quality, flexibility and efficiency in operations.
With a connected shop floor, facilities can support manufacturing 24/7 and improve productivity. Capabilities such as real-time analytics/monitoring, and BI systems can help manufacturers gain enhanced visibility into the processes. They can discover and act on insights faster, while making smarter decisions on the move.
This holistic, data-driven approach can help improve agility and efficiency of manufacturing processes, while maintaining quality and compliance.
Industry 4.0 and Quality 4.0: Two pillars of a smart ecosystem
Quality 4.0, on the flip side, is derived from Industry 4.0. It is defined as the adoption of smart technologies to improve operational efficiency and product quality. Quality 4.0 enables smart systems to integrate seamlessly with traditional systems such as manufacturing execution (MES), enterprise resource planning (ERP), product lifecycle management (PLM), or compliance training systems across the value chain. It enables end-to-end processes that help resolve issues faster.
Analysing operational data (or quality information) enables proactive risk management, by addressing quality issues early on. Real-time quality data can be analysed to increase productivity and allocate resources based on risk and need.