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n.BA.AD.DFP2.24HS (Digital Food Processing 2) 
Module: Digital Food Processing 2
This information was generated on: 12 November 2025
No.
n.BA.AD.DFP2.24HS
Title
Digital Food Processing 2
Credits
2

Description

Version: 2.0 start 01 August 2024

 

Study Programme Applied Digital Life Sciences
Regulations Applicable RPO, 29 January 2008, School of Life Sciences and Facility Management Academic Regulations, 15 Dec. 2009, Annex for the Bachelor of Applied Digital Life Sciences degree programme
Module Type  
  Compulsory Module  X Elective Module    Optional Module
Planned Semester 6th Semester
Module Coordinator Manuel Nüesch
Telephone / E-Mail +41 (0)58 934 58 36 / manuel.nueesch@zhaw.ch
Lecturer(s),
Speaker(s),
Associate(s)
  • Manuel Nüesch
  • Tilo Hühn
  • External speakers on digitization and industrial automation
Entrance Requirements Digital Food Processing 1
Learning Outcomes and Competencies Technical skills:
The students can:
  • Develop modification, revision, and optimization strategies using process analysis (problem-based).
  • Explain how innovative food processes are developed using process and product analysis (solution-based).
  • Evaluate process evaluation relationships from ecological, economic, social, sensory, nutritional, and technological perspectives.
  • Create a functional description for controlling a subprocess.
  • Develop a control concept in collaboration with process engineers.
  • Describe the functional principles of measurement technologies used.
Transferable skills:
The students can:
  • Agilely handle administrative constraints and learn to compensate for them.
  • Deepen their experiences in team building and collaboration in various settings.
Module Content
  • Develop and evaluate innovative food processing processes or subprocesses.
  • Continuous measurement technologies (pressure measurement, NIR, chromatography, pH, temperature, optical methods, etc.)
  • Case studies of continuous process controls.
  • Reverse engineering/subprocess analysis of a standard process to identify process modification options.
  • Functional descriptions.
  • Potential analysis for establishing self-regulating process elements (continuous measurement technology, knowledge-based control (rule-based system), automated thinking (neural network), and their combination).
Follow-up Modules -
Methods of Instruction 
  • Use of the "Blended Learning" concept, including self-directed learning of theoretical content with instructional videos and texts.
  • Use of case studies to apply acquired theoretical knowledge to real industrial challenges.
Digital Resources
  • Instructional videos and texts.
  • Exercise and application tasks in active plenary sessions.
  • E-practicum and exercises.
Lesson Structure / Workload  
 Contact Hours 28
 Guided Self-Study 14
 Independent Self-Study 18
 Total Workload 60
Classroom Attendance Yes: Attendance is mandatory for internships and e-exercises.
Assessment Experience grade 100%: Case study, process presentation, and documentation in the form of a process description and oral examination.
Language of Instruction  English
Comments -

 

Course: Digital Food Processing 2
No.
n.BA.AD.DFP2.24HS.V
Title
Digital Food Processing 2

Note

  • No module description is available in the system for the cut-off date of 12 November 2025.