Shaping your future
EFFICIENT MACHINE LEARNING SOLUTIONS AND PROCESS OPTIMISATION FOR long term SUSTAINABLE COMPETITIVENESs
KDS – Kähm Digital Solutions GmbH
Increasing your efficiency through digitalisation
Everyone is talking about the hype surrounding AI and machine learning, but what exactly can they really do in an industrial environment?
With our experience and knowledge of customised digital solutions for industry, I can help you solve your problems and identify and leverage real potential.
Every production plant and situation is unique and therefore needs a customised solution. We will find your optimal solution together – practical, efficient and future-orientated.
Optimisation of business processes
efficiency increase
with digitalisation
Ensuring your
competitiveness
FROM CONCEPT TO IMPLEMENTATION
Solutions for Your challenges
1. SUSTAINABILITY WITH ENERGY SAVINGS AND RESOURCE EFFICIENCY
By using smart IT solutions, processes can be designed to be more resource-efficient, which helps to reduce energy consumption and the ecological footprint.
- Cost savings of > 1 Mio€ per year by using data visualisation tools
- Predictive Maintenance using machine runtimes and sensor data
2. PROCESS OPTIMISATION THROUGH REPORT AUTOMATION
Operating costs can be reduced by automating and optimising production processes. Our experience is that more and more reports are required on a daily basis, but these can often be easily automated.
- Minimise manual data transfer with automated batch reporting
- Prevent unnecessary system downtime by predicting storage capacity
3. COST OPTIMISATION WITH MACHINE LEARNING
Machine learning, a discipline of Artificial Intelligence (AI), has great potential in the industrial environment. We can work with you to identify which solutions can add value in your environment.
- Improve laboratory efficiency by predicting quality data
- Optimise process costs using machine learning models
WHAT WE DO FOR YOU
Analysing the existing situation
Identification of potential
A clear plan through to implementation
Listen . Find Solutions .
You would like to advance digitalisation in your company? Arrange a meeting
Dr. Walter Kähm
I am a digitalisation consultant for industrial processes from Bonn. Even during my PhD in chemical engineering, I was fascinated by solving process engineering challenges with the help of digital tools and machine learning, a discipline of artificial intelligence. In the course of my professional life in the chemical industry, I have gained extensive experience – both in identifying sustainable solutions and in approaches that offer no added value in practice.
Theory and practice perfectly combined
A sound understanding of the current state of the art is essential in order to remain competitive. But theory alone is not enough – it must be supplemented with practical, process engineering expertise. This is the only way to develop sustainable and efficient solutions.
Over the past eight years, I have worked intensively on the successful implementation of digital solutions in the areas of production, logistics and management. My approach: information must be prepared and communicated in a way that is appropriate for each target group. I find it particularly exciting to find the optimal combination of tool, visualisation and infrastructure for each individual situation.
Optimization for Chemical Engineering and Biochemical Engineering –
Theory, Algorithms, Modeling and Applications
Cambridge University Press, Oktober 2020
During my PhD I had the privilege to work on the publication of this book. This work gives an overview of optimisation methods for various problems in the chemical and biochemical industry.
This book combines over 50 years of experience in the successful application of mathematical methods to industrial problems.
More information can be found here.
Book reviews
‘This book offers a very clear, uncluttered presentation of key ideas of optimisation in rigorous form and with plenty of examples from a decade of research and educational experience. It offers an exceptional resource for educators and students of optimisation methods, as well as a valuable reference text to practitioners.’
Alexei Lapkin – University of Cambridge
‘This excellent book brings together important and up-to-date elements of the theory and practice of optimisation with application to chemical and biochemical engineering. It’s an ideal reference for students on advanced courses or for researchers in the field.’
Nilay Shah – Imperial College
09.2019 – 31.12.2024: Lanxess Deutschland GmbH, Leverkusen
Process Engineer
- Management of digitalisation projects to increase the efficiency of production processes
- Responsible for the new planning of a chemical plant with CAPEX in the double-digit million range
- Modelling and optimisation of existing and newly planned plants
09.2018: Westlake Vinnolit, Gendorf (Germany)
Intern
- Development of a simulation programme for training plant personnel for a chemical reaction within a furnace reactor
09.2017: Westlake Vinnolit, Gendorf (Germany)
Intern
- Development of a simulation programme for training plant personnel for a chlorination reactor
08.2016 – 09.2016: Westlake Vinnolit, Burghausen (Germany)
Intern
- Development of a control concept for a new batch reactor
07.2015 – 09.2015: Westlake Vinnolit, Hillhouse (UK)
Intern
- Development of a calculation tool for a new PVC production plant
- RCA and HAZOP analyses for a batch polymerisation process
08.2011: BASF, Nienburg (Germany)
Intern within R&D
- Analysis of the rheological behaviour of suspensions for the coating of catalysts
07.2011: Chemieanlagenbau Chemnitz GmbH, Chemnitz (Germany)
Intern
- Participation in the commissioning of a pilot plant for the production of petrol from syngas
07.2010: Shell, Wesseling (Germany)
Intern in the laboratory
- Analysing the properties of petrol, diesel and heating oils from production
2016 - 2019
University of Cambridge, Cambridge (UK)
PhD in Chemical Engineering focused on:
- Optimisation of simulated chemical processes
- Intensification and thermal stability of batch reactions
- Advanced process control of chemical plants
2015 - 2019
London School of Economics and Political Science (LSE), London (UK)
Bachelor of Science in Business and Management
2012 - 2016
University of Cambridge, Cambridge (UK)
Master of Engineering und Bachelor of Arts in Chemical Engineering
Grade: Class 1
2010 - 2012
Cambridge Centre for Sixth Form Studies, Cambridge (UK)
A-levels in Chemistry, Physics, Maths and further Maths
Grade: A*A*A*A*
- Optimal control in chemical engineering: Past, present and future
Computers & Chemical Engineering, Volume 155, December 2021 - Robust thermal stability for model predictive control of batch processes
Computers & Chemical Engineering, Volume 130, November 2019 - Thermal stability criterion of complex reactions for batch processes
Chemical Engineering Research and Design, Volume 150, October 2019 - Lyapunov exponents with model predictive control for exothermic batch reactors
IFAC-PapersOnLine Volume 51, Issue 18, 2018 - Optimal Laypunov exponent Parameters for stability analysis of batch reactors with model predictive control
Computers & Chemical Engineering, Volume 119, November 2018 - Stability criterion for the intensification of batch processes with model predictive control
Chemical Engineering Research and Design, Volume 138, October 2018 - Thermal stability criterion integrated in model predictive control for batch reactors
Chemical Engineering Science, Volume 188, October 2018
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