For many businesses, manual assembly continues for form an important part of their production. These sub-assemblies can be an integral part of the final product, so it is essential they are correctly assembled. Integrating manual assembly cells into factory automation systems cannot begin without error free parts. To provide error-free assemblies, guided operator systems (GOS) ensure that operators pick the right parts, in the correct sequence.
The GOS controller signals the operator by indicating the location of the correct component to pick. Control of picking uses various signals or physical barriers on the appropriate parts bin. Signals can be lights, spoken commands or automatic doors to make it obvious to the operator which component to select. Sequenced instructions can also available on-screen, using touch-screen HMIs for operator confirmation and interaction. The structure provided by GOS contributes to error-free part identification, localisation and delivery. Furthermore, it accelerates operator training.
Guided Operator Solutions also allow production orders to be automatically allocated to a manufacturing or picking cell. This provides immediate and visible benefits to assembly operators as well as entire production lines. It ensures delivery of the correct manufacturing schedule to the work area and achieves an almost instant workstation changeover. Manufacturing data sent to the business systems ensures accurate production information is available for OEE calculations, tracking and traceability. Finally, it also minimises errors in manufacturing and logistics operations hence improving efficiency and quality.
Integrating manual assembly cells into production
The GOS controllers automate manual assembly cells that would traditionally exclude them from control and optimisation. They also provide real-time monitoring to production specialists via their ERP and MES systems. Enterprise systems deliver visibility and actionable insight on machinery from these controllers, allowing plants to run more efficiently and profitably.
Increased access to data also drives key performance indicators of the assembly area and provide guidance on improvement strategies. More precisely, fundamental parameters that can be assessed include overall equipment effectiveness (OEE), overall labour effectiveness (OLE), scrap/yield, right first time and re-work, on time in full (OTIF) delivery, rate of return and customer complaints.
Key Performance Indicators (KPIs)
KPI metrics can assist factories in improving the quality and consistency of their products. As fewer defective assemblies reach the market, customers’ complaints, churn and minimising product returns. This, in turn, can lead to substantial growth in both a company’s reputation and revenues.
On the production line, it allows plant managers to identify issues in operator performance and define OLE improvement strategies. Also, controllable are the amount of re-work and associated waste. This leads to a reduction in work-in-progress between processes and can improve its OEE.
Close the integration between a GOS, it’s PLC and ERP system provide greater control over supply chain management processes. By automatically providing correct part bin data, GOS tracks the number of components available and trigger a reorder. Therefore, part replenishment uses real-time conditions, improving inventory management activities.
Furthermore, improved process understanding makes it possible to simplify scheduling operations and component allocation for multi and mixed-model assemblies. Forecasting product demand and part requirements are more reliable, empowering users to become leaner by balancing supply, inventory and demand. As a result, implementing just-in-time delivery and build-to-order strategies are possible without increasing costs of stock and storage.
Improved overview highlights
GOS offers users more than error reduction in integrating manual assembly cells by improving productivity, product quality and flexibility. It integrates with higher-level enterprise systems to positively impact on the entire production facility. It turns manual assembly cells into measurable entities, allowing producers to become more responsive.