Simulating value creation opportunities at inspection processes using digital twins
Lead Research Organisation:
University of Sheffield
Department Name: Advanced Manufacturing Res Centre Boeing
Abstract
The ante-mortem and post-mortem inspection protocols for quality and safety assurance of meat production in UK abattoirs is set out in the operational guidelines of the Food Standard Agency's (FSA) manual for official controls. These official guidelines outline the processes, resources, and reporting protocols used by Official Veterinarians (OVs) and Meat Health Inspectors (MHI) to carry out and file both Ante-Mortem (AM) and Post-Mortem (PM) inspection reports. However, it has emerged from the "Review of 21st Century Abattoirs" by a team of researchers that due to variations in production throughputs, species processed, and kill-speeds across abattoirs in the UK, it is somewhat challenging for the FSA and Food Business Organisations (FBOs) to empirically determine the key resource constraints and Key Performance Indicators (KPIs) of efficient and effective AM and PM inspections routines.
In order to enable inspectors from the FSA and FBOs to discharge their duties more efficiently and accurately, it is imperative to develop deeper insight into the process functionalities and relevant metrics that have direct implications for inspection efficiency, quality and safety scrutiny within abattoirs, which itself is another challenge. However, a thorough analysis is possible to obtain detailed process information through the following:
(1) A detailed map of the process layout/configuration requirements of AM/PM critical control points.
(2) A detailed map of the manpower requirements and standardised operating protocols for AM/PM inspections and reporting by OVs.
(3) A detailed outline of in-process KPIs and constraints of AM/PM inspection processes and reporting
(4) Relative and absolute benchmarking of available technology interventions that can be incorporated to improve the accuracy and efficiency of specific AM/PM inspections beyond what is obtainable from visual checks, palpations and offal incisions.
(5) Evaluation of process capabilities to incorporate recommended technology interventions within a specific process.
While there is scope to augment existing inspection processes, routines and data streams with technologies such as imaging technologies, line-mounted and hand-held sensor technologies, Artificial Intelligence-based fault detection and diagnostic technologies and track-and-trace applications, it is important to carry out a detailed map of the current or AS-IS operating inspection model along the four streams outlined above in order to:
(a) standardise AM and PM inspections
(b) match the right inspection process, resource and technology requirements to abattoirs by throughput, species and kill-speed, and
(c) inform investment in the right layout, process or technology along with right combination of human and technology interventions to usher in an era of 21st century abattoir inspections by the FSA and FBOs.
Practically, it is challenging to determine the effect of technology or process interventions on existing operations. Simulations have been used as a supporting digital technology to trial possible innovations in a risk-free virtual environment before introducing either a new technology or a process. Determination of the future-state requires the digital twin developed in this project to be validated and its viability to be determined. This will be achieved through a series of use-cases where the current state will be modelled and the future case simulated, providing an excellent starting point for the development of a digital twin.
In order to enable inspectors from the FSA and FBOs to discharge their duties more efficiently and accurately, it is imperative to develop deeper insight into the process functionalities and relevant metrics that have direct implications for inspection efficiency, quality and safety scrutiny within abattoirs, which itself is another challenge. However, a thorough analysis is possible to obtain detailed process information through the following:
(1) A detailed map of the process layout/configuration requirements of AM/PM critical control points.
(2) A detailed map of the manpower requirements and standardised operating protocols for AM/PM inspections and reporting by OVs.
(3) A detailed outline of in-process KPIs and constraints of AM/PM inspection processes and reporting
(4) Relative and absolute benchmarking of available technology interventions that can be incorporated to improve the accuracy and efficiency of specific AM/PM inspections beyond what is obtainable from visual checks, palpations and offal incisions.
(5) Evaluation of process capabilities to incorporate recommended technology interventions within a specific process.
While there is scope to augment existing inspection processes, routines and data streams with technologies such as imaging technologies, line-mounted and hand-held sensor technologies, Artificial Intelligence-based fault detection and diagnostic technologies and track-and-trace applications, it is important to carry out a detailed map of the current or AS-IS operating inspection model along the four streams outlined above in order to:
(a) standardise AM and PM inspections
(b) match the right inspection process, resource and technology requirements to abattoirs by throughput, species and kill-speed, and
(c) inform investment in the right layout, process or technology along with right combination of human and technology interventions to usher in an era of 21st century abattoir inspections by the FSA and FBOs.
Practically, it is challenging to determine the effect of technology or process interventions on existing operations. Simulations have been used as a supporting digital technology to trial possible innovations in a risk-free virtual environment before introducing either a new technology or a process. Determination of the future-state requires the digital twin developed in this project to be validated and its viability to be determined. This will be achieved through a series of use-cases where the current state will be modelled and the future case simulated, providing an excellent starting point for the development of a digital twin.
Publications
Cansu Kandemir
(2022)
A Generic abattoir simulation model: bringing the food industry into the 21st century
Shi Victor Guang
(2021)
Developing a generic manufacturing circular economy assessment framework
in International Journal of Production Research
Shi Victor Guang
(2021)
Digital servitization for sustainable value creation
Sun C
(2021)
PhysiNet: A combination of physics-based model and neural network model for digital twins
in International Journal of Intelligent Systems
Sun Chao
(2022)
PhysiNet: A combination of physics-based model and neural network model for digital twins
in International Journal of Intelligent Systems
| Description | This study uses discrete-event simulation (DES) modelling with virtual testing of technology, people, and process configurations to allow the exploration of 'what-if' scenarios to predict and optimise the system behaviour. A generic simulation model of a pig abattoir process flow was developed to provide the FSA with a methodology for visualising how equipping inspectors with technologies could support efficient and accurate operations. In addition, this proof of concept would also contribute to the FSA strategy to deploy the right balance of technology and labour via the new operational transformation agenda. |
| Exploitation Route | A proof-of-concept simulation model is being provided to assess impact of the improvement opportunities. The developed generic simulation model on the abattoir process flow provides insights into how an inspection process can be optimised and then transformed using technologies. It offers an opportunity analysis for the FSA to equip its inspectors with latest technologies to increase efficiency and reduce inspection inaccuracies. In addition, this proof-of-concept has the potential to help the FSA understand the impact of technology intervention at different critical control points to support a strategy for deploying the right balance of technology and workforce for inspections. This study showed the capabilities of DES modelling to simulate where and how interventions can be made to increase the inspection process efficiencies, while optimising the use of resources. |
| Sectors | Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Energy,Environment,Manufacturing, including Industrial Biotechology |
| URL | https://www.food.gov.uk/research/meat-hygiene-research-programme/simulating-value-creation-opportunities-for-fsa-inspection-processes-using-digital-twins?print=1 |
| Description | The developed generic simulation model on the abattoir process flow provides insights into how various abattoir processes including inspection can be transformed using digital technologies. As the model is adaptable, it will continue to help the Food Standards Agency (FSA) to understand the impact of technology intervention at different critical control and inspection points. This will help develop a strategy for the right balance of technology and workforce deployment in a 21st Century abattoir environment. It will guide the FSA to equip its inspectors with the technologies needed to function more efficiently and accurately. In addition, this model can be easily transformed to a digital twin by populating it with live data through appropriate sensors and Internet of Things (IoT) technology. Digital twins - a first for the meat industry - when scaled up, would provide a risk-free platform to observe the current state of processes and experiment with transformation strategies before committing to real investments. For example, the in-depth process data along with scenario modelling would help meat processing companies to understand their process capabilities, efficiencies, and challenges. |
| First Year Of Impact | 2023 |
| Sector | Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Environment |
| Impact Types | Societal,Economic,Policy & public services |
| Description | EPSRC Connected Everything Feasibility Study Part 2 |
| Amount | £80,000 (GBP) |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2024 |
| End | 03/2025 |
| Description | Simulating value creation opportunities at inspection processes using digital twins |
| Amount | £70,398 (GBP) |
| Funding ID | ST/V001450/1 |
| Organisation | Science and Technologies Facilities Council (STFC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 07/2020 |
| End | 06/2021 |
| Description | Digital Enabled Advanced Services |
| Organisation | Aston University |
| Department | Operations and Information Management Group |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | The project applies digital twin technology to the advanced services delivery system enabling manufacturers to model and evaluate the interrelated actors, products and services that together deliver DEAS. The project focus on the case company (a heating system manufacturer) and its ability to assess whether providing 'heat as a service' for its corporate customers is feasible. The case company's ability to assess the feasibility of offering 'heat as a service' and which specific agreements to include in the offer necessitates a detailed understanding of its value delivery system - the processes and resources and external partners to deliver this advanced service to the customer. Identified potential current and future opportunities of applying digital twin technology and simulations to support the case company in assessing the feasibility of its advanced service offerings. Specifically, involve following tasks. • Develop the digital twin requirements and a prototype of advanced service delivery system • Simulate different advanced services and delivery system configurations to assess their implications |
| Collaborator Contribution | Establish the scope of the value delivery system in terms of the assets, actors, processes and data that combine to deliver 'heat as a service'. Identified and prioritize the Case Company's advanced service value propositions and define the criteria for the evaluation using expertise in advanced service value propositions and information system development. Define the information required (incl. currently available and potentially required data sources) to represent the advanced service delivery system. Identified the parameters and KPIs for measurement, the sources of data for measuring them and the interdependencies between them in a dynamic model. Development work on the information architecture, workshops with the case company, validate and further refine the work. The finalised information requirement architecture defined the specification for the development of proof of concept digital twin. |
| Impact | This is a multi-disciplinary project, involving business expertise at Aston Business Schoo in operations and information management in advanced service value proposistions, engineering and computuer science expertise in Advanced Manufacturing Research Centre (AMRC), University of Sheffield and Engineering School, Univeristy of Exester. |
| Start Year | 2019 |
| Description | Digital Enabled Advanced Services |
| Organisation | Baxi |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | The project applies digital twin technology to the advanced services delivery system enabling manufacturers to model and evaluate the interrelated actors, products and services that together deliver DEAS. The project focus on the case company (a heating system manufacturer) and its ability to assess whether providing 'heat as a service' for its corporate customers is feasible. The case company's ability to assess the feasibility of offering 'heat as a service' and which specific agreements to include in the offer necessitates a detailed understanding of its value delivery system - the processes and resources and external partners to deliver this advanced service to the customer. Identified potential current and future opportunities of applying digital twin technology and simulations to support the case company in assessing the feasibility of its advanced service offerings. Specifically, involve following tasks. • Develop the digital twin requirements and a prototype of advanced service delivery system • Simulate different advanced services and delivery system configurations to assess their implications |
| Collaborator Contribution | Establish the scope of the value delivery system in terms of the assets, actors, processes and data that combine to deliver 'heat as a service'. Identified and prioritize the Case Company's advanced service value propositions and define the criteria for the evaluation using expertise in advanced service value propositions and information system development. Define the information required (incl. currently available and potentially required data sources) to represent the advanced service delivery system. Identified the parameters and KPIs for measurement, the sources of data for measuring them and the interdependencies between them in a dynamic model. Development work on the information architecture, workshops with the case company, validate and further refine the work. The finalised information requirement architecture defined the specification for the development of proof of concept digital twin. |
| Impact | This is a multi-disciplinary project, involving business expertise at Aston Business Schoo in operations and information management in advanced service value proposistions, engineering and computuer science expertise in Advanced Manufacturing Research Centre (AMRC), University of Sheffield and Engineering School, Univeristy of Exester. |
| Start Year | 2019 |
| Description | Digital Enabled Advanced Services |
| Organisation | University of Exeter |
| Department | College of Engineering, Mathematics & Physical Sciences |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | The project applies digital twin technology to the advanced services delivery system enabling manufacturers to model and evaluate the interrelated actors, products and services that together deliver DEAS. The project focus on the case company (a heating system manufacturer) and its ability to assess whether providing 'heat as a service' for its corporate customers is feasible. The case company's ability to assess the feasibility of offering 'heat as a service' and which specific agreements to include in the offer necessitates a detailed understanding of its value delivery system - the processes and resources and external partners to deliver this advanced service to the customer. Identified potential current and future opportunities of applying digital twin technology and simulations to support the case company in assessing the feasibility of its advanced service offerings. Specifically, involve following tasks. • Develop the digital twin requirements and a prototype of advanced service delivery system • Simulate different advanced services and delivery system configurations to assess their implications |
| Collaborator Contribution | Establish the scope of the value delivery system in terms of the assets, actors, processes and data that combine to deliver 'heat as a service'. Identified and prioritize the Case Company's advanced service value propositions and define the criteria for the evaluation using expertise in advanced service value propositions and information system development. Define the information required (incl. currently available and potentially required data sources) to represent the advanced service delivery system. Identified the parameters and KPIs for measurement, the sources of data for measuring them and the interdependencies between them in a dynamic model. Development work on the information architecture, workshops with the case company, validate and further refine the work. The finalised information requirement architecture defined the specification for the development of proof of concept digital twin. |
| Impact | This is a multi-disciplinary project, involving business expertise at Aston Business Schoo in operations and information management in advanced service value proposistions, engineering and computuer science expertise in Advanced Manufacturing Research Centre (AMRC), University of Sheffield and Engineering School, Univeristy of Exester. |
| Start Year | 2019 |
| Description | Simulation capability development using Anylogic |
| Organisation | DSE Consulting |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Development of joint technology roadmap for simulation and digital twin development. Identify joint opportunities for future industrial and academic collaborations. |
| Collaborator Contribution | Staff training using AnyLogic Software In kind software license to access to AnyLogic professional. In kind technical support for using AnyLogic and Anylogistix software. |
| Impact | This is multi disciplinary partnership, involving AMRC's capability in engineering simulation and engineering servitization capabilities. DSE Consulting in software development, machine learning and simulation capabilities. |
| Start Year | 2020 |
| Description | Supply Chain Simulation with UK based Battery Manufacturer |
| Organisation | AMTE Power |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | The production of battery cells for electric vehicles (EVs) is a critical component of the EV supply chain. It currently presents several challenges. The production of battery cells requires a complex mix of raw materials, including lithium, cobalt, nickel, and manganese. The supply of these materials is subject to geopolitical risks, with some countries controlling the majority of the world's reserves, making it challenging for manufacturers to secure reliable and cost-effective supplies. It is currently more expensive than conventional internal combustion engines, and cost reduction is a critical challenge for the EV industry to become more competitive with traditional vehicles. Battery cell manufacturing requires high precision, and the quality of the battery cells is critical for their performance. Ensuring consistent quality across production batches is essential to maintain the reliability and safety of EVs. The demand for EVs is growing rapidly, which creates challenges in scaling up battery cell production to meet demand. Increasing production capacity requires significant investment in facilities and equipment. The production of battery cells has an environmental impact, including carbon emissions from the production process and the disposal of end-of-life batteries. Ensuring that the production process is sustainable, and that end-of-life batteries are recycled responsibly, is essential to minimise the environmental impact of the EV supply chain. Overall, the production of battery cells presents several challenges that must be addressed to enable the widespread adoption of EVs. Improving the supply chain's reliability and sustainability, reducing the cost of production, and increasing production capacity are all critical factors in driving the adoption of EVs and transitioning to a more sustainable transportation system. We applied the Anylogistix software to analyse the battery supply chain. This software amalgamates optimisation and simulation techniques to generate a control tower view of the supply chain. Through the simulation environment, users can assess the supply chain's performance in terms of financial, operational, and sustainability metrics, as well as observe the effect of supplier disruptions, implement interventions, and evaluate the supply chain's resilience under stress. |
| Collaborator Contribution | Support data caputre for battery system structure and component level bill of materials. Information relates to supply base location, quantifity for demand, shipment mode. Bi weekly meeting with research team at the AMRC and site visit. |
| Impact | We applied the Anylogistix software to analyse the battery supply chain. This software amalgamates optimisation and simulation techniques to generate a control tower view of the supply chain. Through the simulation environment, users can assess the supply chain's performance in terms of financial, operational, and sustainability metrics, as well as observe the effect of supplier disruptions, implement interventions, and evaluate the supply chain's resilience under stress. |
| Start Year | 2023 |
| Description | Cross High Value Manufacturing Catapult Workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Present research findings to HVMC Supply Chain Sprint workshop, The aim of the workshops is to identify those critical manufacturing sectors and interconnected supply chains for which the UK has an existing or emerging competitive advantage and quantify the scale of the market opportunity. |
| Year(s) Of Engagement Activity | 2023 |
| Description | Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | 9 people attend for a workshop organised by STFC, our project team reported our research findings, which sparked discussions and interest in related areas. |
| Year(s) Of Engagement Activity | 2021 |