Abstract

Digitisation of manufacturing processes under the umbrella of Industry 4.0 is a multi-faceted challenge, with requirements ranging from ensuring all relevant data is captured and has meaning, to combining and analysing data streams correctly, through to creating useful and intuitive real-time user interfaces.

One such data stream that has more recently become of interest due to improved processing powers allowing near real-time, and in some cases real-time analysis, is image data. We will demonstrate as a case study how images can be used to help the pharmaceutical industry in the transition from batch to continuous processing through providing near real-time analysis of in-situ crystal images taken during the crystallisation process.

Traditionally, particle size and shape measurements in pharmaceutical production have been made offline, therefore introducing the risk of altering particle properties during the procedure of taking samples, drying and measuring. More recently, instruments such as the Particle Vision and Measurement (PVM) imaging tool which can provide real time, in-situ, qualitative particle image data have seen widespread uptake both in academia and industry. Here we will show an interactive tool that has been developed with the purpose of providing users of such instruments with quantitative information and statistical data as the crystallisation process develops, allowing control measures to be taken in near real-time.

Combined with other simultaneously-acquired data streams, the quantitative information extracted through the imaging user tool provides both user feedback and also further enhanced control information through the use of the data as input to analysis from other methods, such as the inversion of particle chord length distributions.

This work was carried out as part of the EPSRC ‘Intelligent Decision Support and Control Technologies for Continuous Manufacturing of Pharmaceuticals and Fine Chemicals’ project, EP/K014250/1.

Conference

ConferenceNetwork Plus: Industrial Systems in the Digital Age Conference 2017
CountryUnited Kingdom
CityGlasgow
Period20/06/1721/06/17
Internet address

Fingerprint

Analog to digital conversion
Drug products
Image analysis
Crystallization
Imaging techniques
Industry
Processing
User interfaces
Drying
Particle size
Feedback
Crystals

Keywords

  • particle properties
  • data stream
  • crystal images
  • pharmaceutical production
  • particle vision and measurement (PVM)
  • imaging tool

Cite this

Cardona, J., Ferreira, C. S., McGinty, J., Hamilton, A., Agimelen, O., Cleary, A., ... Tachtatzis, C. (Accepted/In press). Enabling digitisation of continuous manufacturing processes: the role of image analysis. Abstract from Network Plus: Industrial Systems in the Digital Age Conference 2017, Glasgow, United Kingdom.
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abstract = "Digitisation of manufacturing processes under the umbrella of Industry 4.0 is a multi-faceted challenge, with requirements ranging from ensuring all relevant data is captured and has meaning, to combining and analysing data streams correctly, through to creating useful and intuitive real-time user interfaces.One such data stream that has more recently become of interest due to improved processing powers allowing near real-time, and in some cases real-time analysis, is image data. We will demonstrate as a case study how images can be used to help the pharmaceutical industry in the transition from batch to continuous processing through providing near real-time analysis of in-situ crystal images taken during the crystallisation process.Traditionally, particle size and shape measurements in pharmaceutical production have been made offline, therefore introducing the risk of altering particle properties during the procedure of taking samples, drying and measuring. More recently, instruments such as the Particle Vision and Measurement (PVM) imaging tool which can provide real time, in-situ, qualitative particle image data have seen widespread uptake both in academia and industry. Here we will show an interactive tool that has been developed with the purpose of providing users of such instruments with quantitative information and statistical data as the crystallisation process develops, allowing control measures to be taken in near real-time.Combined with other simultaneously-acquired data streams, the quantitative information extracted through the imaging user tool provides both user feedback and also further enhanced control information through the use of the data as input to analysis from other methods, such as the inversion of particle chord length distributions.This work was carried out as part of the EPSRC ‘Intelligent Decision Support and Control Technologies for Continuous Manufacturing of Pharmaceuticals and Fine Chemicals’ project, EP/K014250/1.",
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author = "Javier Cardona and Ferreira, {Carla Sofia} and John McGinty and Andrew Hamilton and Okpeafoh Agimelen and Alison Cleary and Yi-Chieh Chen and Jan Sefcik and Walter Michie and Robert Atkinson and Ivan Andonovic and Christos Tachtatzis",
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day = "23",
language = "English",
note = "Network Plus: Industrial Systems in the Digital Age Conference 2017 ; Conference date: 20-06-2017 Through 21-06-2017",
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Enabling digitisation of continuous manufacturing processes : the role of image analysis. / Cardona, Javier; Ferreira, Carla Sofia; McGinty, John; Hamilton, Andrew; Agimelen, Okpeafoh; Cleary, Alison; Chen, Yi-Chieh; Sefcik, Jan; Michie, Walter; Atkinson, Robert; Andonovic, Ivan; Tachtatzis, Christos.

2017. Abstract from Network Plus: Industrial Systems in the Digital Age Conference 2017, Glasgow, United Kingdom.

Research output: Contribution to conferenceAbstract

TY - CONF

T1 - Enabling digitisation of continuous manufacturing processes

T2 - the role of image analysis

AU - Cardona, Javier

AU - Ferreira, Carla Sofia

AU - McGinty, John

AU - Hamilton, Andrew

AU - Agimelen, Okpeafoh

AU - Cleary, Alison

AU - Chen, Yi-Chieh

AU - Sefcik, Jan

AU - Michie, Walter

AU - Atkinson, Robert

AU - Andonovic, Ivan

AU - Tachtatzis, Christos

PY - 2017/5/23

Y1 - 2017/5/23

N2 - Digitisation of manufacturing processes under the umbrella of Industry 4.0 is a multi-faceted challenge, with requirements ranging from ensuring all relevant data is captured and has meaning, to combining and analysing data streams correctly, through to creating useful and intuitive real-time user interfaces.One such data stream that has more recently become of interest due to improved processing powers allowing near real-time, and in some cases real-time analysis, is image data. We will demonstrate as a case study how images can be used to help the pharmaceutical industry in the transition from batch to continuous processing through providing near real-time analysis of in-situ crystal images taken during the crystallisation process.Traditionally, particle size and shape measurements in pharmaceutical production have been made offline, therefore introducing the risk of altering particle properties during the procedure of taking samples, drying and measuring. More recently, instruments such as the Particle Vision and Measurement (PVM) imaging tool which can provide real time, in-situ, qualitative particle image data have seen widespread uptake both in academia and industry. Here we will show an interactive tool that has been developed with the purpose of providing users of such instruments with quantitative information and statistical data as the crystallisation process develops, allowing control measures to be taken in near real-time.Combined with other simultaneously-acquired data streams, the quantitative information extracted through the imaging user tool provides both user feedback and also further enhanced control information through the use of the data as input to analysis from other methods, such as the inversion of particle chord length distributions.This work was carried out as part of the EPSRC ‘Intelligent Decision Support and Control Technologies for Continuous Manufacturing of Pharmaceuticals and Fine Chemicals’ project, EP/K014250/1.

AB - Digitisation of manufacturing processes under the umbrella of Industry 4.0 is a multi-faceted challenge, with requirements ranging from ensuring all relevant data is captured and has meaning, to combining and analysing data streams correctly, through to creating useful and intuitive real-time user interfaces.One such data stream that has more recently become of interest due to improved processing powers allowing near real-time, and in some cases real-time analysis, is image data. We will demonstrate as a case study how images can be used to help the pharmaceutical industry in the transition from batch to continuous processing through providing near real-time analysis of in-situ crystal images taken during the crystallisation process.Traditionally, particle size and shape measurements in pharmaceutical production have been made offline, therefore introducing the risk of altering particle properties during the procedure of taking samples, drying and measuring. More recently, instruments such as the Particle Vision and Measurement (PVM) imaging tool which can provide real time, in-situ, qualitative particle image data have seen widespread uptake both in academia and industry. Here we will show an interactive tool that has been developed with the purpose of providing users of such instruments with quantitative information and statistical data as the crystallisation process develops, allowing control measures to be taken in near real-time.Combined with other simultaneously-acquired data streams, the quantitative information extracted through the imaging user tool provides both user feedback and also further enhanced control information through the use of the data as input to analysis from other methods, such as the inversion of particle chord length distributions.This work was carried out as part of the EPSRC ‘Intelligent Decision Support and Control Technologies for Continuous Manufacturing of Pharmaceuticals and Fine Chemicals’ project, EP/K014250/1.

KW - particle properties

KW - data stream

KW - crystal images

KW - pharmaceutical production

KW - particle vision and measurement (PVM)

KW - imaging tool

M3 - Abstract

ER -

Cardona J, Ferreira CS, McGinty J, Hamilton A, Agimelen O, Cleary A et al. Enabling digitisation of continuous manufacturing processes: the role of image analysis. 2017. Abstract from Network Plus: Industrial Systems in the Digital Age Conference 2017, Glasgow, United Kingdom.