Services
Services
Building on the methods of mathematical physics, we offer specialist consulting and research support across three areas. In each, our approach places weight on theoretical grounding and empirical verification.
Cleanroom Consulting
Working from models of airflow and particle behaviour, we provide scientifically grounded support for cleanroom design, operation, and cleanliness assessment. Applying mathematical modelling methods developed through particle physics research at Fermilab and SLAC, we work to reconcile the cleanliness a facility requires with the cost of running it.
- Cleanliness class design and airflow simulation
- Mathematical modelling of particle generation and dispersion
- Support for establishing measurement and monitoring
- Improvement and fault analysis for existing facilities
Technical topic
Air change rate and purifier count: two design decisions that move the cost a great deal
Much of what a cleanroom costs to build and maintain comes from its air conditioning and ventilation. How many times per hour the air is replaced, and how many purifiers of what capacity are installed: these two design judgements weigh heavily on both construction cost and electricity cost.
On many projects the tendency is to adopt the upper end of the range recommended by ISO standards. That is a decision made on the side of safety, but when the air change rate or the equipment count runs higher than necessary, both construction cost and day-to-day electricity cost become excessive.
At MPL we model the relationship between particle generation in the room, airflow patterns, and the cleanliness class, and calculate the air change rate and equipment count that are necessary and sufficient to hold the target cleanliness. The purpose of the analysis is to remove overspecification without any loss of yield.
In work carried out as technical advice to the parties involved, construction cost was reduced by up to approximately 70% against a quotation from a major general contractor.
Mathematical Consulting
Across manufacturing, finance, research and development, and beyond, we help solve problems by casting the phenomena involved as mathematical models and applying data analysis and numerical simulation. Large-scale data analysis and statistical methods developed in high-energy physics are brought to bear on practical work.
- Constructing mathematical models and verifying them theoretically
- Statistical analysis and data science support
- Numerical simulation and algorithm design
- Technical advice and second opinions
Technical topic
Replacing prototypes and model experiments with FEM analysis: lower cost, far more conditions verified
Building prototypes and running model experiments in manufacturing carries substantial cost in materials, machining, and inspection time. There is also a limit to how many design conditions can be verified at once.
With FEM (finite element method) analysis, the behaviour of structures, heat, vibration, and fluids can be simulated on a computer with real precision. Because multiple design options and conditions can be verified in parallel without physical prototyping, it is possible to converge efficiently on an optimal solution from the earliest stages of development. Lower prototyping and testing costs, together with a substantial expansion in the conditions that can be verified: both benefits arrive at once.
The reach of FEM is not confined to manufacturing. In agricultural production, the establishment of a technique for reproducing the internal structure of fruit mathematically through FEM analysis, and distinguishing sound fruit from abnormal or defective fruit non-destructively, has been reported in the academic literature. The director of MPL took part in that research as one of its authors, and the paper received the Annual Best Paper Award of the Japanese Society for Horticultural Science. Even where physical experiment is difficult, a mathematical model can open a way in. That is the strength of FEM analysis.
Renewable Energy Research
We carry out research and development in generation forecasting that combines meteorological data with physical models, in system performance evaluation, and in supply and demand optimisation. Using methods from statistical physics and numerical analysis, we support decisions in which uncertainty has been quantified.
- Building and validating generation forecast models
- Performance evaluation of solar and wind systems
- Optimisation analysis of energy supply and demand
- Technical support for R&D and demonstration projects
Not sure which service fits? Ask us.
We will propose the approach that best suits the problem at hand.