Public Funding for Alford Fe Limited

The vision of this industrial research project is to bring from TRL3 to TRL5, SCORE: Supply Chain Optimisation for demand Response Efficiency. This system will enable Tier 1 and Tier 2 suppliers in manufacturing sectors to better manage their inventory through digital technologies and minimise the impact of sudden changes in demand and maintenance activities. The key objectives in fulfilling this vision are to: 1. Ensure smooth flow of materials between different nodes of supply chain 2. Minimise waiting time to start production and avoid delays through tracking of materials at different stages 3. Automate raw material demand according to production cell cycles for production lines to minimise 'on-floor' unused material 4. Integrate continuous a learning-enabled model for prediction of demands and machinery breakdowns The main areas of focus in this project are on implementing the sensors for the track and trace of inventory and developing machine learning algorithms for the creation of demand forecast model and inventory change models. Although enterprise resource planning (ERP) systems take into consideration some factors, e.g. the scheduled maintenance activities, they are mostly generic tools, lacking specialist forecasting systems, and relying extensively on statistical methods for inventory control predictions. The innovation in SCORE lies in the application of machine learning to optimise supply chain management models which traditionally use statistical analysis methods, the integration of different models into one and the communication of the forecasts with the entire supply chain, leading to more precise control over the inventory, greater traceability of assets, and near elimination of delays in supply or overstocking of parts. Our initial target market is the supply chain management (SCM) software market, with Tier 1 and Tier 2 suppliers the target users. This project represents a clear technological innovation for UK SCM, and major growth opportunity for the SME supply chain consortium. To successfully achieve this, the project consortium features the relevant expertise including track and trace system development, machine learning algorithm development, and inventory control expertise.

**Overview** Our Workplace Social Distancing solution will allow people to safely return to work as the lockdown restrictions are lifted by tracking proximity to fellow workers using wearable technology that combines GPS with new indoor GPS and Bluetooth standards to, provide feedback to wearers when they are in each other space via vibration and alerts. **Issue:** Social distancing will prove a challenge to workers and employers alike as the pandemic enforces restrictions on social distancing. In order to lift restrictions, it is likely controls and measures such as distancing will still need to be enforced. These measures will likely be required for some time after any lockdown is partially / permanently removed. Whilst in some industries it will be possible to implement home working, many other professions / jobs will require workers to be on site. This will present challenges in tracking employee contact, movement and even workforce management. Mobile technology for tracking on it's on won't provide instant feedback on distancing and may not be a suitable solution for many workforces based on: \* Phone signal challenges \* HSSE rules preventing carrying use of a mobile device \* Company or even government policies restricting the use of mobile devices in the workplace In addition, accuracy of current mobile solutions would not be sufficient to provide accuracy <2m. **Sectors that will be impacted by social distancing include:** \* Healthcare \* Manufacturing \* Construction \* Warehousing \* Food Preparation \* Community support \* Wellbeing (for example: public gym) \* Wholesale & Retail Trade \* Prison Service / MoD workers **An example of the problem:** The construction sector is one of the largest in the UK economy -- employing 3.1 million people or over 9% of the workforce. The construction sector contributes £117 billion to the UK economy, 6% of total economic output. UK construction and civil engineering is one of the least prepared industries to work from home. Leesman surveyed 19,906 people working in the UK construction and civil engineering space and identified 49% have no home working experience. Our solution will provide highly accurate feedback on distancing and contact points making it safe for workers to resume roles where they need to be present at a work location and will provide additional information about infection and possible community transition. The device will also help workers identify early signs of illness by monitoring key features such as temperature and other vital statistics such as heart rate.