Gaining greater transparency into operations on the shop floor is increasingly critical as manufacturers transform their business models around digital technologies.
Up to this point, the actual production center often presented a gap in coverage. Specialized warehouse management systems covered inventories prior to production with shipping and fulfillment tools tracking final products. Visibility into defects in materials, scrap or similar issues that emerge in the production environment, on the other hand, wasn't as simple.
It is time to eliminate this coverage gap as we enter an era when more organizations are finding ways to automate processes and use data to create value. Automated data collection tools used on the shop floor can empower workers to update inventory levels in real time without disrupting their work, allowing for greater precision and transparency across every phase of operations.
Bringing Visibility to the Shop Floor
The convergence of the industrial Internet of Things and similar trends has begun to transform manufacturing processes to the point that organizations must get seriously about coordinating data and technology across a wide range of operations, Advanced Manufacturing reported.
Gregg Bigleman, TMS tool management solutions manager at Zoller Inc., told the news source that plant management has changed dramatically as complexity makes greater transparency essential.
"I've been involved with manufacturing for 40-plus years," Bigleman told Advanced Manufacturing. "When I started, plant managers were seasoned professionals. The plant manager was an all-seeing, all-knowing god of manufacturing ... [With companies] demanding year-over-year cost downs, you need to know the [plant floor] information, you need to know it's accurate. It can't be done the way it was done in the past with the plant manager walking around with everything in his brain."
Technologies that bring together data from throughout the production environment is increasingly essential. A separate Advanced Manufacturing report explained that organizations are increasingly aware of the need to generate and share information from the factory floor in near real time.
Eliminating the Data Collection Gap
Finding ways to collect data effectively and automatically integrate it with relevant systems, such as a company's ERP, is critical. Production teams can't be inconvenienced by complex, clunky technologies that disrupt their workflows. As such, moving from paper-based data reporting depends on digital tools that are not only easy to use, but also limit risk. RFgen deals with these issues through data collection tools that let users quickly scan a barcode and immediately update backend data using a mobile interface.
These types of solution are particularly valuable in process manufacturing sectors, where regulatory requirements mandate organizations tightly control materials throughout every component of the supply chain. However, the efficiency benefits, such as being able to identify defects and automatically alert the warehouse or notify stakeholders if the wrong product is delivered, are valuable across a wide range of industries.
RFgen can empower organizations to establish a complete framework for product traceability built around simple barcode setups and improve picking productivity through shop floor visibility that reduces the need for mid-production adjustments. Furthermore, organizations can easily check material quantities throughout various steps in the manufacturing cycle to quickly identify any potential problems, such as an extra part or missing supply, before it has an adverse impact on product quality.
The move to data-driven processes is helping manufacturers gain greater visibility into the supply chain, create audit trails across all areas of operations and optimize backend processes that support production teams. Extending these benefits to the shop floor through automated data collection tools takes these benefits to another level by eliminating a longstanding stronghold for paper records and tedious manual processes.