Due to the growing demands and competition in all industries, manufacturers are continuously seeking ways to be more competitive; rethinking their assembly and packaging processes to improve OEE and productivity. In order to achieve this goal, many manufacturers have turned to soft automation (also known as ‘flexible automation’) Vision Robotic Systems which have become a common tool used in processing and packaging applications. With the developments in robotic and camera technology, vision robots are now capable of many complex tasks. Providing high speed efficiency in product handling, assembly, loading and unloading, case/tray packing, and palletizing applications, ultimately improving the flow of the production process and the overall OEE.
Vision robotic systems can benefit the production line, throughout the whole production process, including the final packaging and labelling. As OEE highlights the three major losses in the manufacturing process, we show below how automation through vision robots can improve each of the component parts of OEE.
1. Improving Availability
Downtime loss includes time loss in adjustment, tooling changes, changeover, and so on. Vision robots provide high speed and flexibility to minimize downtime in setup and adjustment. They are capable of handling a variety of products with minimum time lost for changeovers from one product style to the next by simply reprogramming the system, which makes new product introduction more cost effective. Previously, product changeover or tooling changeover could take up to 3 hours, but today’s modern equipment has enhanced that time to perhaps 15 minutes. A vision robotic system, however, can often change over within one minute or less. This significantly reduces down time and improves OEE.
2. Improving Performance
Speed loss includes misfeed, component jams, reduced cycle time and operator inefficiency. One of the features of vision robotic systems is to replace humans to do routine and repetitive tasks, carrying out processes faster and more accurately over sustained periods. It also has the ability to work in challenging environments (such as heat, dust, humidity) without any loss in performance.
3. Improving Quality
Quality loss includes yield losses and defects in process. This loss might be one of the easiest factors to identify but one of the most difficult factors to improve. Broken, bent, and damaged products reduce productivity as well as OEE. With precise vision robotic system, the quality of the products vastly increase. More good products are finished on the first run, and the amount of defects and waste produced as a result of inconsistent finishing are reduced. Moreover, vision robots equipped with machine vision system can also provide inspection & quality control on finished products, which can be more accurate and consistent than manual inspections.
It has been suggested that the world class OEE is 85%, which is a suitable long-term goal for many manufacturers. However there is a wide variation across various industries, for example, Chemical plant, flour mill, machining factory adopt world class standards with an average 94% OEE score; Bottling plants, automotive plant and packing process line usually have lower score of around 75%. As every industry is unique, as well as every company, so it is with every manufacturing process. Consequently manufacturers shouldn’t be too fixated on one standard benchmark, but use OEE benchmarking for monitoring and maintaining their own improvement process.