Embedded Intelligence (EI) requires the use of sensors, communications and processing that are embedded into the product, process or service in order to meet specific objectives. As such, the embodiment of EI depends on a multidisciplinary approach for successful implementation.

Challenges Diagram

All of our projects represent an Intelligent Engineering Application, where the technical strands converge and are consolidated into the delivery of embedded intelligent solutions.

Building on the expertise at Loughborough and Heriot-Watt University our projects seek address challenges across one or more of the following themes;

Design for EI:

  • Effective, robust capture of the application requirements to dictate the specific technology solution sets for the embedded intelligence.
  • Determination of the solution spaces for: sensor modalities (temperature, pressure, acceleration, orientation); communications technologies (wired/wireless, near field, far field, frequency, antenna design, communications network topology); power sources (scavenged, mains, battery); processor selection (with/without, I/O capabilities, clock frequency, memory capacity, power requirements, thermal management requirements, packaging solution);
  • Multi-variable design trade-off techniques, balancing the cost, quality, time and effectiveness of embedded intelligence solutions;
  • Design of standard platforms of hardware and software on an open-research basis.

Intelligent Software:

  • Semantically model relationships between the embedded chips and environmental data;
  • Derive necessary performance techniques that enable systems to be optimally designed for reliability, with an intelligent diagnostic and prognostic capability;
  • Provide an intelligent information infrastructure, requiring multi-layered ontologies that will have to be researched, designed and constructed to deal with the large volume of terse data sets;
  • To enable effective, reliable and resilient cross-system integration;
  • Deriving ontologies with a layered approach, providing direct mapping to data stores to aid with cataloguing the vast volumes of real-time terse data from embedded systems;
  • Incorporating the dynamic relationship between data sets and models developed from applications, e.g. manufacturing processes (e.g. utilising existing BPM);
  • Ensuring compatibility of the semantics between source and target systems, e.g. aided by use of XML;
  • Developing semi-automated node and linking techniques to increase efficiency and ensure system adaption to changing situations;
  • Providing feedback into the ontology and the system to provide new ontological links and update existing data;
  • Interrogation of the ontology to determine the critical quantifiable lifecycle process characteristics that relate to the inherent performance drivers, allowing rapid identification of significant factors and complex interactions, and show overall system performance;
  • Evolving ontologies to provide an adaptive integrated Bayesian network infrastructure that will be used to analyse overall system performance and predict areas for optimisation.

Service Systems:

  • The development of on-demand 
intelligent product lifecycle service systems
    Effective specification, design and creation of the complete service system, including:
    • Service Foundations
    (e.g., dynamically reconfigurable architectures, data and process integration and sematic enhanced service discovery);
    • Service Composition
    (e.g. composability analyses, dynamic and adaptive processes, quality of service compositions, business driven compositions);
    • Service Management and Monitoring
    (e.g. self: configuring, adapting, optimising etc.)
    • Service Design and Development
    (e.g. engineering of business services, versioning and adaptivity, governance across supply chains);
  • Understanding service and lifecycle requirements with technological infrastructures to support integration and co-operation of components and services.
  • Optimisation of the services to enable improved efficiency across the product lifecycle, entailing better resource utilisation, increased productivity and reusability, improved product quality and reliability and maintainability, prolonged service life, and decreased costs.

Manufacturing Solutions:

  • Exploiting process consolidation through co-creation of products and EI features, e.g. antennae or electrical interconnect, by means of additive manufacturing and assembly of electronics and sensors to embody light-weight, high performance EI into products, processes and operational environments;
  • Enabling cradle-to-cradle approaches for remanufacturing, recycling and re-use, by means of intelligent processes interrogating products at their end of life, identifying through-life history and BOM;
  • Developing novel manufacturing solutions, e.g. emerging from nature-inspired propositions. Biomimetics and biomorphism lend themselves to disguising EI devices and systems, to adding multifunctionalities or, to enhancing operational capability by novel processing of substrates; Mechanobiological solutions (e.g. stress-indicating bacteria) and at different scales (e.g. self-assembly nanowhiskers) will push the boundaries of EI devices and systems manufacture beyond traditional approaches.
  • EI in processes will allow development of Industry 4.0 features, allowing communications between processes and products during production, providing opportunities for closed-loop optimisation of processes to products and vice versa.

Packaging & Integration/Interconnect:

  • Matching packaging technologies to volume demand, ensuring cost, quality and resilience for all levels of packaging – chip, system-on-chip (insert), module level (e.g. wirebonds, flip chip), chassis to chassis (cable, flex or wireless);
    Design of antennae structures and dielectric builds for robust wireless communications;
  • Matching design partitioning of functionality onto components / chipsets selection and packages for cost, size and compatibility;
    Low-cost integration of packaging solutions with current manufacturing processes, e.g. placement and interconnection of chips within PCB during fabrication requires assembly and joining processes not normally found at a PCB fabricators facility;
  • Determining assembly methodologies compatible with the surrounding product matrix for interconnections that will need to be robust to withstand any subsequent processes.
  • High yields at all stages since encapsulation (e.g. overmoulding, ultrasonic lamination) or sealing within an enclosure can lead to difficulty in reworking;
  • Reliability and resilience of packaging and interconnection solutions for the end-use lifetime.
  • Development of advanced packaging at wafer level and for 3D interconnects, which is critical for enabling higher integration, new design freedoms, smaller device footprint, lighter products, reduced signal inductance and higher I/O density;
  • Materials for thermal matching, novel materials, Cu vs Ag (i.e resource efficiency).

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Loughborough University

Wolfson School
Loughborough University
Loughborough, Leicestershire
LE11 3TU
United Kingdom