Designed for industry, made real by innovators

The Made Smarter Technology Accelerator Industry Challenge Owners have worked to define and scope challenges that our cohort of startups will address through technology prototype development. As a manufacturing and challenge focused programme, applications must meet one of the challenge briefs.

On this page you’ll find an introduction to each of the challenges and can click through to read more on each challenge owner and their challenges.

Challenge briefing webinar – catch up and watch the recording here, with presentation and questions from each Industry Challenge Owners.

Introducing the industry challenges

Welcome to our industry challenges, below you’ll find a list of all the challenges open for startup applications

Babcock International Group

Babcock International Group is a provider of critical and complex engineering services to customers across defence, emergency services and civil nuclear.

Babcock challenge: Warrior base overhaul

Babcock provides critical, complex engineering services in the UK and internationally. It delivers vital services and manages complex assets on behalf of public bodies across three key markets; defence, emergency services and civil nuclear. For this challenge Babcock International is looking to assess, develop and deliver a joined up system that provides a digital twin to feed into the Warrior Armoured Fighting Vehicles Overhaul.

Babcock challenge: Digital shipbuilding

Large scale modular construction projects (including shipbuilding) use state-of-the-art computer aided design (CAD) modelling and analysis during the design stages. However, this valuable information is often lost or does not get translated efficiently through to the equipment and personnel on the manufacturing shop floor. Babcock is looking to develop a process to enable specific 3D data from a ship design model to be fed to the point of use using appropriate software and hardware. with consideration to; new ways of presenting complex design data on the shop floor and new ways of managing data access, version control and change management.

BAE Systems

BAE Systems provide some of the world’s most advanced, technology-led defence, aerospace and security solutions. It employs a skilled workforce of 85,800 people in more than 40 countries.

BAE Systems challenge: Scalable artificial intelligence for visual inspection

BAE Systems is interested in an artificial intelligence (AI) vision inspection system which can, once proven, roll-out as a validation assistance tool across various assembly, manufacturing and build stages. This will encompass image categorisation, for build verification and quality checks, and inform go/no go decisions. The solution will need to be extremely quick and easy to train up and deploy, requiring minimal datasets to run, as well as scalable to new assemblies and build stages.

BAE Systems challenge: Dynamic workflow management

This challenge seeks to develop a manufacturing scheduling and workflow management capability that can dynamically react to disruptions and changes through: automatic updates to different variables including supply chain disruptions, resource availability and production status optimised real-time scheduling and replanning. The prototype should aim to mitigate the impact on production informed advanced scheduling for future planning across the supply chain. The solution can leverage or build on supply chain connectivity and IIoT, and the exploitation of data.


As a Standard Industries company, GAF is part of the largest roofing and waterproofing business in the world. With customer-driven innovation, the company has protected homes, businesses, families, and communities for over 130 years. GAF is committed to making our products better, stronger, safer and in more sustainable ways that are faster and easier to install.

GAF challenge: Asphalt material characterisation

GAF is interested in developing a technology based-solution to characterise, identify and understand the critical to quality (CTQ) results and parameters (material, spectral or otherwise) associated with asphalt materials so as to inform downstream manufacturing procedures for a more dynamic process. The prototype will be used to predict and train models on how the ingredients are varying over time and, in turn, be used to inform modifications to the manufacturing process.

GAF challenge: Machine vision systems for product conformance and machine condition

The manufacture of high quality roofing shingles is significantly important to GAF in terms of market recognition and reputation. It is a complicated and high speed operation involving many variations. GAF is looking to employ machine vision and sensor technology to assess product conformance to specification; thresholding and characterising surface anomalies and identifying the process conditions when they occur; and evaluating critical machine components for continuance of use and end of life.

Northumbrian Water

In the North East of England, NWL trades as ‘Northumbrian Water’ in the supply of potable and raw water and the collection, treatment and disposal of sewage and sewage sludge.

Northumbrian Water challenge: Sewer blockages smart Porcupine

Sewer blockages are a real challenge as they cause a significant proportion of sewer flooding, in turn, unflushables in the sewer network are a key contributor to sewer blockages. Northumbrian Water previously developed a device called ‘Porcupine’ which is placed in the sewer and traps unflushables on its spines. Northumbrian Water is looking to develop a ‘smart’ device which can react to issues before they form a blockage or cause flooding.

Northumbrian Water challenge: Water network monitoring and real time analysis

Northumbrian Water wants to improve its visibility and understanding of water quality within a designated district meter area (DMA). For this challenge it is looking to develop a workable sensoring regime within the DMA which would help monitor and manage water quality, flow and pressure in near real-time. In turn helping identify and notify potential and actual leaks within the system.

O’Neills Irish International Sports Company Limited

O’Neills is the largest sportswear manufacturer in Ireland, employing over 800 staff across the island. Established in 1918, O’Neills specialise in the design, manufacture, personalisation, and supply of performance multi-sportswear globally.

O'neill's challenge: Product customisation - intelligent verification

O’Neills production process and ordering systems allow customers to select from and customise a wide range of garments and styles. Customers can achieve a high level of customisation selecting the individual sport, kit style and colouring. For this challenge O’Neills is looking for solutions that can be embedded along the production line at key stages to continuously monitor not only the quality of the product but verification against the approved computer aided design (CAD) models.

O'neill's challenge: Automation of production

Over the last 40 years O’Neills has transformed the production process for garments. O’Neills is keen to implement digital transformation across the production line. In particular to explore how next generation connected robotics and artificial intelligence (AI) can combine to enable higher degrees of automation in the sewing and stitching process, with consideration for the solution to be integrated with existing machines and any fabric constraints.

Safran Landing Systems

Safran Landing Systems is the world leader in aircraft landing and braking systems. It is a partner to 30 leading commercial, military, business and regional airframers. It supports more than 31,200 aircraft making over 73,000 landings every day. Company capabilities encompass the full life cycle of our products, ranging from design and manufacture to in-service support, testing, repair and overhaul.

Safran challenge: Adaptive scheduling and performance monitoring

Safran Landing Systems is an international high-technology group, operating in the aviation (propulsion, equipment and interiors), defense and space markets. Safran’s operations in Gloucestershire focus on three main areas; large landing gear machining, medium machining and special processes. The medium machine manufacturing process specialises in a diverse array of product families requiring a range of unique and bespoke machines. Safran is interested in developing a dynamic scheduling system which can provide an intelligent rules based system capable of reacting to changing customer demand.

Safran challenge: Implementation of SPC on all test rigs in the assembly shop

The operation and maintenance of test rigs is an essential component of Safran Landing Systems’ assembly shop. The rigs are dedicated to one product each, covering the testing of complete landing gears (nose and main) and some detailed parts. Safran would like to explore advanced technology solutions that can provide better visibility both in terms of the test rig performance and those influencing the test results. Integrating an intelligent way to control parameters, monitor routines and implement preventative measures.


Offering delicious great quality food at competitive prices has been at the heart of what Sainsbury’s does since John James and Mary Ann Sainsbury opened the first store in 1869. Today, inspiring and delighting our customers with tasty food remains the priority and Sainsbury’s purpose is clear – driven by a passion for food, together Sainsbury’s serve and help every customer.

Sainsbury's challenge: Microbial control in ready to eat foods

Sainsbury’s is looking to develop solutions to guarantee the absence of specific bacteria in ready to eat products sold in its stores. The ambition is to work in partnership with food producers to contain the problems early on in the value chain, before delivery to Sainsbury’s. The solution must help identification and potentially inactivation of specific bacterial species either on raw material or finished product at point of pack without altering the appearance, taste or nutritional properties of the ready to eat foods.

Sainsbury’s challenge: Increasing shelf life and sell through of products while reducing waste

The drivers of food spoilage and reduced shelf life are relatively well understood, yet  food manufacturers fail to maximise shelf life and quality of food on a consistent basis, this is as a result of both supply chain and raw material complexities. Sainsbury’s is interested in the development of real-time data collection and interrogation mechanisms, and data based automated feedback and control loops that would allow inter-relationships to be identified and managed along an integrated supply chain. 

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