Scott Innovation Hub UpdateIn parallel with developing new products, connecting our machines and building reporting systems, our Innovation Hub activities include building skills. In this update we share news about both new products and skills. Here we introduce two new products. Firstly we’re excited to introduce our Compact Robot Palletiser. This adds to our materials handling offering, sitting alongside our recently announced small payload Cobot Palletiser but with capacity less than our Pal 4.0. It’s a great option when space is constrained. Our second product is our Bin Picking solution, designed for bracket-loading into an appliance manufacturing line, but with a much broader potential application. Our new Bin Picking solution was developed by a new Graduate with R&D capability support from the NZ Government. It uses machine vision and machine learning. Machine vision has been at the heart of many of our products for over a decade and machine learning is a newer capability that is adding to the performance of our machines, as discussed below. COMPACT ROBOT PALLETISER One of our recent developments, the Scott Compact Robot Palletiser provides flexibility to palletise a range of products efficiently and accurately. The compact design enables integration into existing production areas, allowing installation and commissioning with minimum disruption. The flexibility of the design offers either single or double cell options and customisability that ensures a variety of products can be palletised using standard pallets. The Compact Robot Palletiser can palletise up to 30 cartons per minute and up to 80kg per pick and comes with IIOT capability via Ethernet, allowing line operators to monitor the equipment as well as data collection. BIN-PICKING ROBOT Another of our latest developments is a robotic bin picking unit with a cycle time of less than 10 seconds for metal parts. While the task performed by this example is relatively unassuming, the software and ‘brains’ behind the system are important features that can be applied to a wide range of applications and systems going forward. RGB-d data is used to select parts for picking and is able to determine if parts are upside down or not, and adjust accordingly, while machine learning aids its decision making process. Template generation is performed using SolidWorks interface for easy repurposing. RESEARCH AND DEVELOPMENT CAPABILITIES Our new bin-picking solution has me reflecting on the impact R&D Careers support provided by the NZ government has had over the years. The grants have allowed us to bring in new highly qualified, Masters and PhD’s level graduates, providing graduates with the opportunity to find their feet with the application of new skills to new products. Today, several years on from the first grant, the reporting system on our Meat Machines and the Cut Quality-Control tablet are standard products. In fact both were the start of our Industrial Internet of Things reporting systems. More recently the grants have extended our Real-time machine vision applications, established an Augmented Reality (AR) framework and allowed us to apply Machine Learning. The bin-picker is our most recent add on but it will soon be followed by new in-house developed AR Service tools. The additional bonus is that virtually all of the graduates stay on at Scott, so a win-win. |