Industry Case Studies
| Pilot Solution | Status | Description |
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Deployed |
Tracking the status of machinery by reading outputs on legacy display panels in a factory (e.g. dials, lights, and LCD displays), using a Raspberry Pi and low-cost camera. |
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Deployed |
Tracks jobs when they leave and arrive at company sites so that store managers can track which site a particular job is at. |
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Deployed |
Monitors the temperature of wax at intervals during a production process providing live data feed to enable live monitoring and visualisation of the process. |
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Departmental Job Tracking |
Deployed |
Scans job cards to track which department a job is currently in so that the sales people can inform customers of progress and floor manager can detect delays and ensure that jobs don't get lost. |
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Pick and Place Utilisation Monitoring |
Deployed |
Monitors the utilisation of key assets by detecting their state (active, idle, off) using the output from light stacks. |
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Unified Change Management |
Deployed |
Tracks and captures changes on a project, giving users notifications when new changes are introduced to the project. |
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Quality Management |
Deployed |
Allows users to add new quality issues while performing their tasks on site or in the office, assign these issues to a person to be solved and track whether they are resolved or not. |
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Deployed |
Tracks jobs by scanning barcodes at each workstation and capturing the process times of jobs at the main workstations. |
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Offline Voice-Activated Vending Machine |
In Development |
Enables voice activated use of vending machine which aims to reduce the transaction time of vending process and concurrently track inventories in the machine. |
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Braiding Angle Measurement |
Deployed |
Monitoring the quality during production of a braided material and alerting operators when the braiding angle is outside a given tolerance. |
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Digitised Work Instructions for Quality Inspectors |
In Development |
Making quality record information available and searchable from a central repository. The information has to be dynamically extracted from a traditional record store maintained on an excel workbook. |
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Digitised Work Instructions for Operators |
Deployed |
Making process information selectively available to the factory floor workers from a central process information record repository. The information has to be dynamically extracted from a traditional record store maintained on an excel workbook. |
One company keen to explore how digitalisation could help improve productivity is family-run manufacturer Buchanan Orthotics, which makes modular, bespoke and specialist footwear for clients such as the NHS.
After working alongside the Shoestring team to assess needs and develop a solution that easily bolts onto their operations, the company is now piloting a job tracking solution.
Where the company previously used a paper sheet to track orders through the system, low-cost scanners are now being used to digitise the location and status of jobs. This cross-site job tracking pilot enables workers to print tracking labels, record when a job enters and leaves the facility using barcode scanning, and then store all these records centrally in the cloud, so that live job progress can be viewed at any time.
This simple but effective solution demonstrates the combination of openly available and other low-cost off-the-shelf software technologies to collect and record typical manufacturing activities observed on a shopfloor. Management is able to see where all the jobs are in the queue and how they are progressing; ensure no orders are lost or misplaced; identify capacity issues for technicians; advise customer job status; and see jobs close to completion.
Read the full case study >> CLICK HERE
Business challenge
This medium sized manufacturer uses equipment controlled by legacy panels that interface with shopfloor staff to indicate current operational status, using lights, dials and seven-segment displays. The company wants to enhance their existing manufacturing processes by automating the data collection of the current operational status, but in addition have real-time access to the operational status of the machinery. Consequently they need to convert the panel’s visual variable readout into digital data without modifying any processes. This will also facilitate a more accurate analysis of historical records of manufacturing operations to improve planning while linking the digitally acquired data to other associated processes.
The solution
A low cost vision system was built and set up facing the legacy equipment panel of interest. This system comprises a USB camera connected to a credit card sized microcomputer. In this way, the camera feeds are processed in real-time to capture changes across the panel components, e.g. light going on/off. This status change is formatted and presented on a digital dashboard which is also used to adjust and configure the vision system settings. While this low cost vision system solution meets and addresses Photofab’s needs, it can be quickly reconfigured or adapted to work with a variety of control panel models and makes found in other manufacturing companies.
See how one of Shoestring’s partners implemented a Shoestring solution to digitalise data from a legacy panel in their factory.
Business challenge
This medium-sized dental product manufacturer needed to be able to monitor a wax forming process to pre-empt problems caused by temperature changes. They needed to be able to check that wax is being cooled at the right rate to avoid hardening too fast and causing defects in the final product.
The solution
A low cost temperature sensing system was built and set up across one production line. This involved placing a number of non-contact sensors along the production line to collect the temperature readings of the wax at specified intervals. In the first instance the temperature data was collected at 30 second intervals from one sensor and stored using a microcomputer. The data generated was displayed through a digital dashboard, which was also used to adjust and configure the sensing system settings, such as the intervals at which the data was automatically collected. Once proven that the system enabled live monitoring and visualisation of the wax production process, the company rolled it out across the shopfloor. More sensors and microcomputers were added to the other production lines, these were connected to the existing, more powerful microcomputer and, by adjusting and reconfiguring the sensing system via the dashboard, the system can now monitor several production lines simultaneously.
For more information watch the short video at the top of the page
Business challenge
This construction manufacturer was keen to start digitalising their processes but unsure of where to start. The digital needs assessment workshop revealed that a top business priority was to know the production status of doors across the shop floor at any one time. With health and safety considerations paramount for fire doors, job tracking could also play a key part in recording the provenance of each step in every door’s manufacturing process.
The solution
To keep it simple at first, the tracking was set up initially at the first and last workstation for the door manufacturing process as well as at the packing location. Using a different bar code scanner at each location, the doors were scanned as they came off the first production line, scanned again as they went through the final process when the door frame was built, and then scanned when they were packaged. All the details from the scanners were transmitted to a central RaspberryPi set up on the shop floor next to a monitor which displayed a dashboard showing the progress of every job. This has given the company much more visibility of what is happening on the shop floor at any one time. It has also helped them improve their systems so that they can track jobs more effectively going forward. Their next steps are to roll the tracking across the rest of the door production workstations and add another modular Shoestring solution – Digital job cards.
Read the full updated case study >> CLICK here
