UK’s Leading Leather Manufacturer Has Better Data, Better Results10 min video / 11 minute read
- Tags: 96,139
- Screens: 24
- Clients: 8+
- Alarms: 5
- Devices used: 2x Allen Bradley PLCs
- Architectures used: Standard
- Databases used: 2 – MsSQL & 1 MySQL
- Historical data logged: Records for up to 1.4 million hides per year (up to 2.4 million rows per year)
The project allows Scottish Leather Group to track rawhides through an intake fridge system, and categorizes these hides based on their food grade, weight, gender, origin and status to intelligently fill the fridge rails. An outfeed selection algorithm helps operators choose the best available hides for a given fridge outfeed job (i.e. lime processing, recirc, etc.).
The project utilizes two in-house custom-built modules to conquer challenges faced in functionality (client USB camera, and 2D/3D charting), and has built-in analysis and reporting tools for management users.
The goal of the project is to give SLG more useful information on the quality of their incoming product and to give better granularity for hide tracking, much earlier on in the processing of the product, in order to increase end product quality and reduce the defect rate.
Scottish Leather Group had very little storage for fresh rawhides before they’re processed, so the company embarked on a project to build an intake fridge system. The PLC can move hides to any of the 25 rails but cannot make decisions on which rail to use. Ignition with a database was required to make these decisions.
Other challenges included:
- How to track an individual hide or group of hides
- How to efficiently categorize hides for regulatory and other purposes
- How to inspect and take photographs of hides for supplier queries
- How to select the most appropriate hides for the next process
The solution was to utilize RFID tokens for the hooks that hold each hide. By associating the hide with an RFID token, SLG can detect and store information about a hide from initial entry until it leaves the fridge system. Processes further down the factory line can use the job information to see a hide’s journey.
The system has four RFID readers on the infeed, and four on the outfeed side. On the infeed, a hide must be stamped, inspected, weighed and then entered into the fridge. A script is triggered at each of these points to create/update a hide record as it progresses, with the rail intake script consulting the database to find the most appropriate rail to use for the categorization used. On the outfeed, a hook will always be seen at the outfeed weigh scales and the recirc RFID point, but only hides that are to be processed by a lime drum or to be salted for later use are seen at the final two RFID points.
Ignition’s SDK helps at the inspection point, where an operator can choose from five inspection quality questions and needs to be able to take photographs of the hide and store them for later reporting. This was achieved using a custom module built by SLG that allows the client to access a local USB camera; an IP camera was not suitable in this case. The operator just needs to press the capture button and the photograph is saved and assigned to that hide. Any number of photographs can be stored against each hide. It’s very intuitive.
At any point, a user can view the Rail Status page to see the rail location of each hide, along with an information view for each rail detailing each hide in the order they were entered.
When an outfeed job is created, an operator can choose to reject, reorder, drum process, or salt process a group of hides. When the operator starts a job, the system uses a set of unique algorithms to present the operator with a selection of hides that best match what they need, based on the stock available in the fridge. These algorithms must do/consider the following:
- Ignore matching hides that are behind incompatible hides on the same rail
- Always match the food category
- Match gender
- Match contract state
- Match the origin and weight categories, but allow for a mixture if stock levels don’t give an exact match
- Match quantity but with a tolerance if the available hides are slightly less than the number required
- If the quantity of hides doesn’t reach the required number, then do the above but by weight instead
- Not exceed a maximum weight, regardless of hide count requested
Ignition’s versatility and ability to allow users to easily manipulate databases made this possible. Other SCADA packages would have had real trouble with even some of the basic functionality necessary for this project.
Reorder jobs allow the operator to select an option to automatically suggest rails to reorder. This is an algorithm that looks at the current rails and chooses nearly empty and mixed rails to reorganize and unlock stock for easier selection. Mixed rails are only created when stock levels are high and no other option is available at intake.
Reject jobs record the outfeed weight of each hide, and then drop the hides into a reject bin.
Zip files of all photos and commercial documents associated with a delivery, and a spreadsheet of their hide data can be easily created in one action. This gives SLG a useful export for quality and compliance records. This, along with the 2D/3D charts available to them, showing current stock statuses help them utilize the fridge as much as possible.
Chris: I'm Chris Taylor, Managing Director at BIJC Limited. BIJC is a Premier Integrator of Ignition by Inductive Automation. We specialize in SCADA and MES solutions for manufacturing and data centers. This project was to track raw stock from delivery through to initial processing with intermediate smart storage by connecting multiple PLCs and customer databases.
Craig: I'm Craig Hunter, Asset Key Engineer at Scottish Leather Group. Scottish Leather Group creates the world finest sustainable leather for the world's most respected companies. SLG are the UK's leading leather manufacturer and are home to the finest leather makers. The Scottish Leather Group required this project as a way to automatically sort incoming raw stock into the new refrigeration storage to minimize additional process and have smart utilization of the stock for further processing. The project was to sort and store our raw incoming product using key defining characteristics such as weight, gender and supplier into our new refrigeration unit. Once stored, the system was required to extract the raw product into the more suitable batches for further processing.
Jonathan: My name is Jonathan Taylor and I am the Technical Director at BIJC Limited. BIJC is a Premier Integrator of Ignition by Inductive Automation. We specialize in SCADA and MES solutions for manufacturing and data centers. This was a challenging but rewarding project to work on. The project was not only to track and trace raw product, but also to record and present new information on the quality and consistency of received product. By making on-the-fly decisions based on data and inputs from PLCs and various internal customer data sources, the project enables better utilization of the processing capacity. The product is tracked by RFID tokens on hooks, and there were initial challenges in retrieving the data so that it would synchronize with product placement. During development, Ignition's extensive logging allowed us to track where there were any delays allowing us to devise a scheme to only act upon good quality data from the RFID readers.
Craig: The benefits of a project like this are having the product organized ready for processing in batches that will dramatically improve our product quality. The use of pair hide identification and database storage dramatically improves our understanding for further product development and improvement.
Chris: The system is able to automatically categorize raw product into groups that enable better quality processing, reduced environmental impact, better quality data, and new data on supplier quality and consistency, which has not been available in real time before. In the case of this project, Ignition's ability to manipulate data from a database is hugely important. The project would fail without this ability as virtually all decisions the project makes are database driven. Ignition is a great fit for this project as it can easily interface with PLCs, databases and APIs. The Perspective Module allows us to develop browser-based clients and the SDK allows us to develop bespoke additional features.
Jonathan: The project relies on the excellent scripting functions available in Ignition, these are used for both initial sorting and product selection, where an operator is offered various choices for any particular request. These choices include best fit options where the exact request is not available, and the system will automatically fit requests within downstream constraints to improve product quality. For this project, the most important features of Ignition are its ability to manipulate data from multiple databases. The SDK, as it allowed us to develop bespoke modules and Perspective as it allowed us to create contemporary and intuitive web-based screens. Ignition's SDK was required for the creation of two modules that augmented the functionality of the project. The first module allows Perspective in a Windows client to use a local USB-connected camera to preview and save inspection images to the database, all with one button press.
Jonathan: This was very important for the product throughput, inspection, quality data and cost saving. The second module allows Perspective to use the Plotly charting library, we use this to display 2D and 3D charts to help visualize a breakdown of available stock in their various categories. This module is available on the third party showcase to the Ignition community free of charge.
Jonathan: This is the main overview of the project, it gives operators a high level view of stop levels and batches available for initial processing. For more detail, the operator will go to the rail status page. This page shows a detailed view of the stock on each rail in the refrigeration unit, along with the categories associated with the highs on the rails. An operator can get further information on a particular rail via the information icon. This is information about the weights, stamps and order of each hide on the rail.
Jonathan: When a user needs a visual representation of the stock, they can go to the fridge content page. This page contains a Sunburst pie chart from our free-to-use charting module, it shows a quick breakdown of stock levels based on each hide's categorization. Operators can also view a 3D weight distribution diagram to check that sorting is correct. With this, it is easy to see that hides on a rail are sorted correctly as outliers on a rail will be very visible. After a delivery has been important from SLG's internal systems and their commercial documentation is approved, an operator can select the delivery to become active. Final checks can be made on the delivery detail and once accepted, the delivery begins. When a delivery begins, the operator is taken to an inspection screen that tells them which hide is at the inspection station. Here they can choose to inspect the hide and record any defects found. It is here that the second module is used. This module enables access to client connected cameras, and will store images against the hides records so that reports can be made on inspection quality. The camera has been blanked over for this demonstration.
Jonathan: Let's take a look at the current out-feed batch. Here we can see the status of a test batch that is going to the processing drums. Operators can see the hides on this batch that are yet to be exiting the refrigeration unit here. We will cancel this job and look at our options for a new job. We will select this out-load job and see our options for the batch. As we can see, there is not enough stock for an exact match, but the system can still make an option available to the operator. This is all designed so that smart decisions can be made. Let's take a look at some reporting analysis. In this analysis, we can see the total hides in our test data broken down into a high-level comparison of weights, this can be broken down by all suppliers or individual suppliers, so that any potential trends can be captured. Individual delivery reports can be generated via the delivery report page. This will display metrics associated with the delivery along with all commercial and inspection photographs, they can easily be downloaded as a zip file.
Craig: We've worked with BIJC for a number of years on other projects, but this was the most complicated so far. The project was technically challenging, but BIJC were responsive and supportive throughout the development process.
Chris: The project assists in reducing processing costs and producing a higher quality product, which contributes to an excellent return on investment. Ignition is the only SCADA software that BIJC use that has a fully documented SDK. This allows us to offer excellent value by producing unique modules to overcome pain points in customer projects.
Jonathan: Ignition was a great fit for this project because of its flexibility, it was no hassle to try new approaches to challenges without impacting on development time. Ignition also has great connectivity out of the box without worrying about licensing.
Craig: Ignition has helped us better understand complex manufacturing problems using real-time and historical data. Additionally, its simplicity has helped for rapid deployment of projects that were previously too complicated for our other systems.
Created By: BIJC
BIJC is a Premier Integrator from the UK and has been using Ignition for many years. They specialize in both manufacturing and electrical SCADA systems, and have the capability in-house to create specialist Ignition modules, particularly for Perspective. Their systems have been installed in energy, banking, food and beverage, textiles, and non-profit healthcare sectors.
Project For: Scottish Leather Group
Scottish Leather Group has been the UK’s leading leather manufacturer and home to the finest leather makers for centuries. They create the finest automotive leather for some of the world's most renowned cars from the Ford Model T to the DeLorean DMC-12, Aston Martin V8 Vantage to the McLaren F1. SLG is one of the world's lowest-carbon leather makers.