Blispect for pharmaceutical producer – BIOFARM

BIOFARM is a Polish pharmaceutical manufacturer with a long tradition.

The client expected full integration of the machine vision system with the blistering machine while maintaining the existing functions of the blistering machine.
At KSM Vision, thanks to the smart construction and customized hardware of the Blispect system we managed to meet these requirements – integrating the Blispect vision system with the CAM and IMA blistering machines while maintaining operations at full efficiency.

The BLISPECT system implemented at BIOFARM offers:

– inspection of tablets and capsules packed in blisters
– two-color capsules and capsules with prints

The solution prepared for BIOFARM meets GAMP-5 & Audit Trail requirements.

  • Solution BLISPECT
  • Client BIOFARM
  • In our opinion, the use of neural networks and the function of classifying detected defects distinguish the KSM Vision solution from competitive solutions, and the effectiveness achieved by the system ensures quality control at the level of systems of leading manufacturers.
    MLEKOVITA, 1 of 100 biggest Polish private companies 2022 according to Forbes
    M.A. Engineer Dariusz Sapiński,
    President of the Board
  • When designing the solution, KSM Vision showed great flexibility in adapting the system to the expectations of the BIOFARM Production Department. (...) Since the implementation of BLISPECT vision technology on the 1st BIOFARM production line almost two years ago, the KSM Vision Service Department has been available to BIOFARM employees with a good reaction time.
    BIOFARM Jarosław Pieczuro,
    President of the Board
  • KSM Vision Sp. z o. o. has developed a system for quality control of glass vials for pills. (...) A big advantage of the system is the use of machine learning algorithms, which allows easy adjustment of the system.
    ADAMED Group Dariusz Stępień,
    Dyrektor ds. Infrastruktury i Mediów

Project scope

The BLISPECT system integration at BIOFARM service included:

– designing a solution to maintain the functionality and efficiency of the existing blistering machine
– using an proprietary image visioning solution base on the neural network architecture – thanks to that training the system for new formats takes a minute
– use of feature extraction based on neural networks for the analysis of two-color capsules and printed capsules
– detection of defects in size as small as 15% of the tablet/capsule surface
– controlling the sensitivity of the system using only one parameter “tolerance”, which sets the threshold between good capsules/tablets and defective ones
– minimizing line changeover time while maintaining the accuracy of data analysis
– very easy to use system which translates both to faster introduction/training of new operators, and production downtime reduction
– integration of rejection stations for defective products


Our R&D on the solutions with the use of neural network potential are backed by our renowned partners: