< Back When to Hire, When to Hold: Making Smarter Staffing Decisions through Marginal Analysis 21 Nov 2025 It is easy to stay in the abstract when talking about supply and productivity. Yet, at which point does adding more people stop increasing value? It’s something that it is dealt with quite often in the world of modelling and optimisation. At first, additional hands boost efficiency because tasks can be specialised and workflows improved. But eventually, physical space, equipment, technology or processes become the limiting factor and that’s where diminishing marginal returns set in. What is fascinating is how clearly this shows up when you visualise it with marginal product and average product curves. These tell you where efficiency peaks, where it plateaus, and where hiring more actually makes things worse. And this is exactly where modelling, simulation, and data-driven forecasting shine. Before a company commits to new staff, new equipment, or new investment, it can explore “what if?” scenarios safely, spot bottlenecks, test assumptions, and make decisions with far more confidence. Organisations that bring a product or service to the market, whether a small local hair salon, a multinational corporation, or even a government providing public services must make a few key decisions about their offering, such as for instance the price to attribute to the good/service and the quantities to supply If you are a local hairdresser, you likely already have a very good understanding of the going rate for your services, and through basic observation of other salons you can gauge how to operate and how to organise tasks among your staff. However, when we look at the entire economy for a particular good or service, the exercise grows much more complex. So what motivates a company to supply the market with a good/service? There could be different reasons such as gaining market share but profit is a very important driver. Companies make a profit when the price of a good/service is larger than the cost of producing it. When costs are low, and productivity increases, the incentive to expand production grows due to the rising profits. Vice versa, if the costs increase and productivity is low, firms become less motivated to produce at the current market price, instead they might decide to either reduce output or charge higher prices to protect the profit margins. Productivity is pretty much a measure of efficiency, measuring how efficiently inputs are converted into outputs. Better/improved technology and/or working methods tend to increase productivity enabling business to produce even more with the same or even lower amount of resources, therefore decreasing the cost per unit of each output. This increases profitability. Let's take the example of a hair salon deciding on the number of resources to employ (the variable input). With 5 stylists, a total of 115 clients are served in a week, averaging the output to 23 clients per stylist. The output keeps on increasing with every additional new input of labour. This goes on until a new additional input does not result in any additional output. This could be because the salon can take only so much styling chairs due to limitation of space. So businesses expanding their workforce will likely see output growing at first, due to specialisation. If we take the example of the hair salon, instead of 1 employee juggling colouring, cutting, cleaning, dealing with consumers etc., each employee can focus on the area they are best at, thus increasing efficiency. Having said that this has a ceiling since with more additional workers added to limited/fixed workspace/equipment, the gains from adding another resource starts to shrink, until at some point there are zero gains. This is known as diminishing marginal returns. The only way to push past this is to increase the fixed inputs. With our hair salon for instance we could take over additional space allowing more styling chairs. This shifts the production frontier outward. The Marginal Product (MP) curve shows the extra output created by each extra unit of labour. The point where the MP and Average Product (AP) curves intersect i.e. where MP equals AP is where the additional output is exactly equal to the average. At this point, the AP stops increasing and reaches its maximum. Operating at a point where MP = AP is the highest output per worker, and so an indicator of efficiency. MP and AP curves help companies with hiring decisions as it helps identify maximum labour input efficiency, therefore the profit-maximising number of employees. It enables companies to understand when to hire more resources and when to hold. These curves also help companies avoid a stage where MP is 0 or also in the negative. A negative MP is usually caused by too many workers employed with a fixed capital. In our example when too many hairdressers are employed in a confined space with not enough styling chairs, workers start getting in the way of each other leading to a reduction in output. Therefore, this leads to inefficiency and losses. Modelling, simulation, and data science offer powerful tools for understanding and optimising these economic relationships. Using techniques such as discrete event simulation, agent-based models, or machine-learning forecasting, firms can explore how changes in labour, equipment, technology, or pricing affect output long before they commit resources in the real world. These methods help reveal bottlenecks, quantify the impact of productivity improvements, and test “what-if” scenarios such as hiring additional staff or adopting new equipment without disrupting day-to-day operations. For economists, these tools provide richer insights into how supply behaves under different conditions, enabling more accurate predictions of market responses and more informed decision-making for businesses and policymakers alike. Previous Next

< Back Harnessing the Power of Optimisation 12 Mar 2025 We have all been there, seeing a process and thinking, there must be a better way to do this, even achieving a better, more accurate output. It could be a software flow, a manual process or even an entire system, optimisation helps businesses in finding and implementing improvements resulting in a huge impact to the business. Certain processes can be far too complicated when they do not need to be. This means that resources’ time is wasted leading to sub-optimal productivity within a Company. The more complicated processes are, the higher the risk of human errors and setbacks, thus holding Companies back from moving projects and innovation forward, and focusing on what really matters. Every system has its own pace, but when inefficiencies start to negatively affect a Company, it is a good idea to pause for a moment and take a closer look at the different components and tools in place and see where optimisation can make a real change to your business. Process Optimisation can truly help business make that transformation, enabling teams to focus and spend their time and energy on what’s important. Optimisation can bring about a number of benefits to companies and can be used across all sectors, be it public policy, governmental planning, pharmaceutical, biotechnology, transportation, mobility services, manufacturing and operations, FMCG, supply chain and logistics, healthcare, medical applications and finance, just to name a few. To understand Optimisation one has to first understand Predictive Modelling. In Predictive Modelling, as long we know the input x , the relationship between x and y (or f(x)), we are able to predict the output, y . You might be familiar with the below example from your school days, which illustrates the equation of a straight line; y=mx+c , where m is the gradient (or slope) and c is the intercept. In process optimisation m and c could be your process settings. Here, by knowing x and f(x) ,you are able to predict the output, y . Graph showing correlation between x and y So, taking the example above, Optimisation comes in when you need to know m and c , by knowing your input ( x) and what you want to get out ( y) . Therefore, starting from the desired output ( y ), a known variable, we need to understand the relationship between x and y , i.e. f(x) , which are unknowns. We do this by utilising the data that is known by us. Therefore, Optimisation is when you find out what variables you need to deploy and in what manner, in order to get to the desired result or output. Optimisation works by attempting various iterations or value changes in the unknowns (in this case, m and c, our process settings), and varying these until we reach what is called a zero loss (0 Loss) and hence achieve the desired output, y. In this way, we are discovering the parameters needed to get to the desired y. Optimisation can be single-objective or it can be multi-objective, with the latter having more complexity which might make obtaining a 0 Loss very difficult. In such cases, one finds what is called the global minimum, which essentially is the closest possible to a 0 Loss scenario. In Optimisation, a specialised algorithm is used to run the simulations, according to a set of chosen rules and weights attributed to the different rules. Let’s take for instance a multi-objective process Optimisation in a manufacturing setting. Imagine a number of different ingredients which need to be combined together, each bearing different pricing, processing time, and various constraints. A specialised algorithm helps in determining the variables and how these are to be deployed in order to get to the desired product / output. So, this means the best possible product, manufactured within a certain time, cost and of a certain quality. With a Random Sampling technique, when working on such large number of variables and permutations, the higher the number of samples or iteration runs, the closer you get to a 0 Loss, and therefore the more accurate the output. This however leaves the probability of finding the global minimum up to chance. With a Bayesian Optimisation technique we can reach the global minimum in a much more focused manner, taking many less iterations to do so, especially in a multi-variate scenario, making it a more preferred method for Optimisation. Previous Next

< Back The Science and Value of Finite Element Analysis (FEA) in Food Packaging: Food packaging plays a crucial part in complex supply chains (Part 2 of 2) 11 Jun 2025 Behind every sealed lid, there is a world of science and simulation, where temperature shifts, compression forces and impact drops are tested in a virtual setting, before the physical prototype is built. This enables precision and removes the guesswork, in order to bring to your homes food that is safe, fresh and intact enabling high quality products. The future of foods is about smarter design to reduce waste, increase performance and take faster decisions. Last week, in our article "The Science and Value of Finite Element Analysis (FEA) in Food Packaging: Packaging is more than a mere container for your food product. (Part 1 of 2)”, we spoke about how FEA can help companies make better decisions as to which packaging design to go for, when considering various variables. Today we are going to give a more practical example of how food packaging plays a fundamental part during supply chains, to ensure the product arrives safely on our tables at home. Let’s take as an example that we are designing packaging for a chilled ready meal that needs to be transported across a regional supply chain to be sold to supermarkets for the end-user to enjoy. The conditions are that the product is to stay below the 5 °C, remain intact during the various transportation stages, as well as that it has a short shelf-life of 7 days from end of production to consumption. Through Finite Element Analysis or "FEA", we can make use of thermal modelling to understand the behaviour of the meal during the different shifts in temperatures during different transportation, loading and unloading and storage scenarios. It helps us to predict how well the design of the packaging insulates the product across various conditions and temperatures. By creating a virtual model and run simulations, you can compare various materials to understand thermal conductivity and insulation and assess whether additional packaging design features such as layers and vacuum sealing are needed for extra protection. Through FEA’s structural analysis and simulation you understand how the packaging will endure stressors such as stacking in a warehouse by applying virtual compression and impact forces to see whether it survives the pressure, what happens if the product is dropped from a certain height and whether the seal will hold under different pressures. As you see the behaviour, you can tweak and optimise the design such as for example the packaging’s thickness, creating stronger corners, reinforcing the lid but optimising this in such a way to balance out additional protective features and not waste excess material. It is finding the right balance of costs, quality and sustainability, as well as finding the balance of what is the lighter, lowest-cost material to meet the needed requirements. Other considerations are also factored in such as will the packaging fit securely in standard crates for the handling by retailers, how will the design of the packaging fit on a pallet, will its shape and its rigid form allow automated handling in a warehouse and how will it fare under different temperature shifts. By using data-driven and physics-based modelling and simulation early in the development process you can reduce the number of physical prototypes needed, reducing packaging failures and take faster and more informative decisions on the right design of packaging to choose in line with business, technical and sustainability goals. This improves cost, quality and time to make food systems better. Packaging development process becomes a proactive and strategic process, rather than a trial-and-error based exercise, which places a burden on companies and societies. It is way of a smarter exercise to understand how you can deliver to your consumers, in the right manner. Funis Consulting works at the intersection of R&D and Innovation through the use of modelling and simulation techniques. Whether it is understanding new materials, improving robustness or costs-efficiencies of your current design or systems or reducing environmental impact through smart design, the opportunities for meaningful change in foods and food systems are there and they are vast. We believe in a better way to do things, to create real-world impact for a better world. Previous Next

< Back Strategic decision-making under resource constraints - moving "beyond the curve" 05 Nov 2025 In every economy resources are limited, whether that is land, human, capital.... Modelling is about defining those limits and exploring possibilities. The Production Possibilities Curve (PPC) captures this trade-off: It shows what is feasible. In order to move "beyond the curve", systems need innovation or efficiency gains and simulation helps us test how, before actioning this in the real world. It helps with quantifying opportunity costs and reveals the shape of trade-offs. Every scenario is a choice between competing objectives, and optimisation then becomes a story of priorities and constraints. In the end modelling isn't just about computation, but it is about decision-making made visible. Resources are finite in all economies... from land and labour to capital and technology. So, when a country decides on its strategy, it must also decide how to allocate these limited resources across competing activities. This is therefore an optimisation problem; how can we achieve the greatest possible outcome given the constraints? Let's simplify and pretend that our economy is a two-good economy, where you can either manufacture easels or produce oil. If all the resources were dedicated to the manufacture of easels and no resources were allocated for oil production, the economy would produce a maximum of 200 easels. Vice versa, i.e., if all resources were allocated to the production of oil only, there would be 170 units. These are the trade-offs and can easily be visualised with a Production Possibilities Curve (PPC), shown below. The PPC is a basic and fundamental economic concept and it shows the maximum combination of two goods that can be obtained with limited resources and technology. Along the curve of the PPC, resources are used at full productive efficiency. Producing more of one good can be achieved by producing less of the other, because of the limitation in resources. This is the opportunity cost. In the example below, if I produce an additional 20 units of oil, the opportunity cost is 15 easels less. But the question is what if society wants to become more productive? As we have seen before with the resources at our disposal, it is simply not possible to "go beyond the curve". This is only achieved through economic growth, typically driven by things such as investment in capital goods or technical advancement. So, society decides to forego producing easels in favour of new technology or new equipment, as this decision will, in the future, increase the productive capacity of the economy (therefore "moving beyond the curve"). The decision to do this has what we call distributional implications, in the sense that such decisions (e.g. whose consumption is being reduced now and who will benefit in the future), are not evenly distributed amongst societies. For instance, an artist might prefer to have his easels now, whereas a mother with young children might prefer to forego the easels. Economics is not a simple matter of numbers and models, but there is also ethical, policy considerations as well as the preference of society. To conclude, the Production Possibilities Curve (PPC) mirrors the logic of modelling and simulation itself, where you define your constraints and explore the feasible space, you evaluate trade-offs between competing objectives and use analysis to inform strategic choices. Understanding such economic fundamentals help frame simulations not just as computational exercises but as decision-making tools grounded in the real-world dynamics of scarcity, efficiency and growth. Previous Next

< Back Glassy state or plastic state? Moisture control is key for consistent quality in food products. 15 Oct 2025 Why do biscuits lose their crunch? When foods absorb moisture, their glass transition temperature (Tg) drops, triggering a shift from a glassy (hard, brittle, stable) state to a plastic (soft, flexible, less stable) one. This is why crisps go soggy, or biscuits soften. Interestingly, ingredients like corn starch help raise Tg, which is why cereals or crisps can stay crunchy a bit longer even as they absorb moisture. Moisture uptake also creates preferential conditions for microbial growth, reducing both quality and shelf life. Controlling moisture is key to texture, safety, and stability. Through modelling and simulation, we can identify weak points and test solutions virtually, before making the first prototype. Foods often lose their characteristic crunchiness as they absorb moisture, because the glass transition temperature (Tg) is lowered. When this happens, a series of physical, chemical, and microbiological changes can occur, leading to reduced quality and shelf life. Crisps lose their crunch, and biscuits soften. Moisture absorption can trigger phase transitions, shifting foods from a glassy to a plastic state at room temperature. What does this mean? In the glass phase, a food’s amorphous components are in a hard, brittle, and stable state (below Tg). When temperature rise above Tg, or enough moisture is absorbed to lower the Tg to below storage temperature, these components move into a plastic phase, becoming softer, more flexible, and less stable. Foods like dried pasta, candy, and crisps are typically in the glassy state, with low molecular mobility. Once they transition to the plastic phase, they become rubbery, sticky, and may even collapse structurally. This phenomenon is familiar in breakfast cereals, crackers, and fried chicken. Here, starch plays a role in elevating Tg, which helps maintain crunchiness even as moisture is inevitably absorbed. Ultimately, controlling moisture is crucial for maintaining texture, safety, and shelf stability. Through modelling and simulation, it’s possible to identify potential problem areas and test different solutions virtually before the first prototype is created. Multiple scenarios can be simulated rapidly and cost-effectively, exploring possibilities that would be difficult or expensive to test physically. Previous Next

< Back Modelling Complex Chemical Reactions in Dynamic Systems through Reaction Kinetics (Part 1 of 2) 23 Jul 2025 How do chemical reactions unfold in real-world processing environments? Not in a neat, well-mixed beaker, but dynamically, with changing temperatures and concentrations, and multiple physical processes at play. That is where Reaction Kinetics meets Computational Fluid Dynamics (CFD). In food processing, for instance, understanding reaction rates is essential. From flavour development in roasted coffee to shelf-life stability in sauces, these reactions shape quality, consumer appeal, and even energy use. In this article, we explore how modelling chemical kinetics particularly in complex reactions like the Maillard reaction and coupling them with CFD can reveal powerful insights. Whether it's for designing new formulations or optimising thermal processes, this integrated approach helps bridge the gap between lab theory and industrial reality. In dynamic systems such as chemical systems, reactions occur between a number of chemicals. Here reaction rates rarely stay constant and the rate of each reaction is intricately tied to both temperature and the concentration of reactants. As these variables change, for instance with a rise or fall of temperature or the reactants levels decreasing, the increase in concentration of the products with time will vary constantly, so the rate at which products form continuously changes. Understanding and predicting this behaviour is critical, particularly when dealing with complex reactions or processing environments. This is where Reaction Kinetics comes into play and how modelling can help. Reaction Kinetics, also called chemical kinetics, is the study of the rates of the chemical reactions, meaning how fast reactants get converted into products, as well as the factors affecting those rates. So, with Reaction Kinetics we can understand how fast a reaction happens, what influences its speed and what steps and mechanisms are involved in the reaction transformation. In industries such as food processing, reaction kinetics help predict how long to cook, mix or store a product to achieve the desired result such as colour, flavour, shelf-life as well as to help avoid unwanted changes such as the loss of nutrients or flavours which are off. This is where reaction rate equations come into play. These mathematical formulations allow scientists and engineers to describe how fast a reaction proceeds under given conditions. For simple reactions, these equations are relatively straightforward, but in reality, many important chemical transformations are anything but simple. For instance, let's take one of the most common reactions, the Maillard reaction. This is a staple in food chemistry and this type of reaction is responsible for the browning and the flavour of cooked foods. The Maillard reaction is not one single reaction but a cascade of coupled reactions involving sugars, amino acids and heat. The pathways of the reaction can branch, loop back and create a wide variety of end products depending on how conditions evolve over time. The end product can influence not only the colour and aroma but also the sensory perception and hence consumer acceptability of the final product. To model such a Reaction Kinetics system properly, one must take into consideration multiple and often interdependent variables that change simultaneously. In food processing, for instance, the roasting of coffee beans or cocoa involves spatial and temporal temperature gradients, moisture migration and the evolution of volatile compounds, all of which shape the final sensory profile. And when these reactions occur in environments where other than the chemical reactions taking place there are also physical processes, such as mixing, the challenge increases further and that is where tools such as Computational Fluid Dynamics (CFD) get extremely valuable if not essential. CFD allows us to simulate how fluids move and mix over time and by coupling CFD with Kinetic Models of chemical reactions one can begin to understand how physical mixing influences reaction rates, and possibly vice versa. Let's imagine that we are developing a new beverage formulation. In the production process, during mixing, not only it is very important to achieve homogeneity but also to control reaction pathways and the latter is done to stabilise colour, to manage flavour development or avoid unwanted browning. Another example would be the production of thermally processed soups or sauces, where you would need to model the interplay between mixing, heating and chemical transformations, such as for instance acid-base reactions, degradation of aroma compounds, to help optimise the product quality while reducing energy input. When you combine and integrate Chemical Kinetics with Computational Fluid Dynamics (CFD) a powerful avenue opens up that allows you to predict and optimise processes in fields ranging from food science, to pharmaceuticals, to combustion and materials engineering. It enables a more realistic and detailed view of how complex reactions unfold in dynamic, real-world settings which goes beyond the simplicity of a well-mixed beaker in a lab. Previous Next

< Back The Science and Value of Finite Element Analysis (FEA) in Food Packaging: Packaging is more than a mere container for your food product. (Part 1 of 2) 04 Jun 2025 Food packaging is more than what meets the eye. It is indeed about branding, shelf appeal and sustainable endeavours by the manufacturers but at its core, packaging is a way to deliver food in a fresh and safe manner to our tables. It is a delivery system, grounded in science and engineering ensuring chemical stability and mechanical durability. With Finite Element Analysis (FEA) modelling and simulation we can design a virtual prototype and test against stressors and conditions such as drops, temperature shifts and humidity, in order to optimise and ensure that the material is geared for performance. For many of us the term "food packaging” immediately conveys the branding of a product, the convenience to carry a product fresh and safely, from the manufacturer to the consumers’ tables as well as the material’s sustainability element. Packaging gives the ability to companies to communicate with their consumers playing a major role in how a product is perceived - does it resonate with your consumers, does it have a differentiating factor, does it tell a story, does the product convey your sustainability efforts, is it “attractive” to your target segment? All of this is valid, but beneath it all lies a world of science, engineering and innovation that makes packaging one of the most critical components in our food systems. Food packaging is primarily a delivery system. Imagine having to sell orange juice to end consumers on the other side of the world without anything to contain it in. Impossible as far as the laws of physics allow. Packaging provides protection for food from physical damage during transportation and must be convenient to store, open and reseal. From a scientific perspective, food packaging considers chemical stability of the material to the structural integrity enabling food to arrive to our tables in a safe, fresh and intact manner. Besides, there is an increased importance to also do so sustainably. Science provides a balancing act of material science, physics and food chemistry. Packaging needs to provide a barrier against moisture, oxygen, lights and microbes, as well as must avoid unwanted chemical interactions. Modelling and Simulation through Finite Element Analysis (FEA) allows us to test, iterate and optimise packaging designs before the prototype is even created. With this technique you can simulate compression, drop and impact under various stressors which the product may experience during logistical conditions, it evaluates how packaging is protecting the food product under different temperature and humidity levels, it optimises features of the packaging such as its thickness, its seal and its shape to reduce material usage, thus being cost conscious, but without compromising on safety and freshness. FEA helps in identifying failure points and tackle them as well as to understand degradation patterns over time, ensuring environmental impact is in line with the company’s sustainability goals. The technique helps us to understand the behaviour of the packaging design during complex supply chain scenarios, such as for instance temperature-controlled logistics, or stacking in retail settings. Nowadays focus on sustainability is also important to factor in when designing packaging and innovation is about thinking of its entire lifecycle, such as whether packaging can be made from renewable or low-carbon materials, how lightweight it is, thus minimising fuel usage and costs during transportation, whether it can be reused or disassembled as well as how it protects food from spoilage therefore reducing food waste. All of this whilst thinking also of other factors, such as keeping food safe and delivering food products of high quality and freshness as well as keeping overall costs down for companies and end consumers. Innovation in food packaging is a multidisciplinary approach involving a complex system which benefits greatly from modelling and simulation techniques to guide better decisions. Previous Next

< Back Of Force Fields and Simulations: Whether it’s All-Atom (AA), United Atom (UA) or Coarse-Grained (CG), a good Force Field is a cornerstone in Molecular Dynamics 18 Jun 2025 Not all Force Fields are created equal and in Molecular Dynamics your results are only as good as the Force Field behind them: the set of rules how atoms move, bond and vibrate! Whether you go all-in with an All-Atom (AA) Force Field or speed things up with a Coarse-Grained (CG) approach, choosing the right Force Field is crucial for a delicate balance of accuracy, efficiency, detail and scale. There is no such thing as a universal Force Field, which can be applied for everything. However, a well-chosen, well-tested Force Field? Now that is what turns a simulation into a real insight. So, choosing a good Force Field is paramount for success. In Molecular Dynamics, the accuracy of the results of your simulation depends entirely on the quality of the model that you are using. This means that the equations and the parameters describing how the system behaves needs to be of a high quality within the model that you are using. These equations and parameters are what makes up the Force Field. A Force Field consists of two main parts: the mathematical function (equation) which estimates potential energy (like how atoms bond or repel each other) and the parameters used within those functions. These methods fall under molecular mechanics because they only take into account the positions of atomic nuclei, ignoring the more complex behaviour of electrons and such simplification makes the Force Field simulations much faster than quantum mechanical ones, yet producing impressively accurate and precise results. There are a number of Force Fields out there, but none of them are a one-size-fits all kind of Force Field. Therefore, we have different Force Fields designed for different purposes such as if we want to simulate small organic molecules, proteins, lipids or polymers, or different environments such as water, membranes or vacuum. Terms such as all-atom (AA), united atom (UA) and coarse-grained (CG) Force Fields denote the level of detail that the Force Field works with. AA Force Fields simulate every single atom, giving you fine detail but at a higher computational cost. UA Force Fields on the other hand simplify things by grouping aliphatic hydrogens with their carbons therefore reducing the total number of particles, while CG Force Fields takes it a step further by grouping several atoms together (e.g., three carbon atoms and their hydrogens) into what’s called a single “bead” or superatom. Going from AA to UA to CG what you’ll do is that you will lose the detail but on the other hand gain huge improvements in computational power, therefore making CG methods especially useful when dealing with large systems. Such systems could be simulating the behaviour of thousands of molecules, each with hundreds of atoms, making running a detailed AA simulation impractical. There are plenty of Force Fields to choose from and popular ones include OPLS-AA , OPLS-UA , AMBER , CHARMM , MARTINI and COGITO just to name a few. Which one to go for very much depends on your system, your goal and how long you would like to wait for the results. Given that no one Force Field can work for everything. Some are more versatile than others, but in most cases you will need to test and validate your chosen Force Field, ideally by checking whether it can reproduce known experimental results before diving into your full simulations. In the end a Force Field is a powerful, yet simplified tool. Even when using basic models such as for instance bond stretching with Hooke’s law, it can still provide a surprisingly accurate picture of the real system. One of the key strengths of a good Force Field is transferability. This means that the Force Field should not only perform well on specific molecules it was built for but also on related or larger systems. This is what makes a good Force Field a valuable cornerstone of molecular simulation. Previous Next

Contact Funis Consulting Ltd if you have any questions.

Find the answers to the most frequently asked questions about Funis Consulting Ltd's services and how we work. Frequently Asked Questions Read our frequently asked questions. If you cannot find the answer to your question here please send us an email on info@funisconsulting.com or Contact Us What does Funis Consulting offer? At Funis Consulting, we focus on two main areas: 1. Scientific Computing We specialise in advanced modelling and simulation, helping businesses solve complex challenges with precision and efficiency. Our expertise spans: Chemistry and Physics Modelling – from understanding how chemicals behave under specific conditions to simulating entire manufacturing processes. Data-Driven and First-Principles Models – leveraging statistics, data analysis, AI, and machine learning, or physics-based methods such as: - Molecular Dynamics (MD) - Thermodynamics - Reaction Kinetics - Computational Fluid Dynamics (CFD) - Finite Element Analysis (FEA) - Smoothed Particle Hydrodynamics (SPH) - Discrete Event Simulation (DES) - Discrete Element Modelling (DEM) We also provide code optimisation, parameter/process optimisation, and data analysis & visualisation. These are often embedded within the models we build but can also be delivered as standalone services. Funis Consulting develops tailor-made scientific software as well as solutions built on off-the-shelf tools. Being software-agnostic, we integrate seamlessly with a client’s preferred programming language or platform. Our work combines strong scientific expertise with data science and high-performance computing (HPC), including GPU-accelerated applications. 2. Scientific Consultancy We provide specialist consultancy in chemistry and physics, with a strong focus on the FMCG and food manufacturing industries. Using modelling, simulation, and technology-driven approaches, we support clients in: - Research & Development - Product formulation and innovation - Process optimisation - Shelf-life study design and analysis - Regulatory compliance and market alignment Our Core Services: - Scientific software development (custom solutions) - Process & parameter optimisation - Data analysis & visualisation - Mathematical, physical & chemical modelling - Process modelling - Code optimisation & HPC - Machine learning & AI integration - Model-based scientific consultancy (chemistry & physics) for FMCG and food manufacturing Industries We Serve: While FMCG and food manufacturing are our primary areas of expertise, our methods apply broadly across: - Flavours & fragrances - Pharmaceuticals & healthcare - Banking, finance & economics - Transportation (automotive & aerospace) - Utilities & government departments - Manufacturing, energy & environment - Agriculture - Research & academia What core services do you offer? The core services offered by Funis Consulting are: - Custom Software Development ranging from scientific applications to business tools - Process & Parameter Optimisation to enhance efficiency through advanced algorithms - Data Analytics & Visualisation to transform complex data into actionable insights - Mathematical, Physical & Chemical Modelling to develop high-precision simulation - Code Optimisation & HPC: We can work with both CPU as well as GPU for superior performance - Machine Learning & AI Integration to drive innovation through smart automation - Scientific Consulting for FMCG by building models to assist in new product development to food chemistry insights. What kind of project engagement models do you offer? We offer flexible project structures to suit businesses of all sizes. Our approach can be fixed-cost or time-based, depending on your specific needs. Plus, our first online consultation, to understand whether Funis Consulting is for you, is always free, with no obligation. If you’re facing a complex process challenge or have a modelling or data project in mind, talk to us to see how we can help. What we do is quite niche and we are entrusted with projects by a variety of clients and partners ranging from innovative start-ups to global multi-nationals and leading experts in their fields. Talk to us if you need more information and take a look at some of our clients and partners by going on our homepage. Which industries can make use of your services? We can work across many industries including, but not limited to FMCG, flavours and fragrances, pharmaceuticals and healthcare, banking, finance and economics, transportation including automotive and aerospace, utilities and government departments, manufacturing, energy, environmental and agriculture, research and academia. Not sure whether we can help the nature of your business? Don’t worry, drop us an email and ask us, or fill in the contact form we shall get back to you as soon as we can. How can my business benefit from Modelling & Simulation? Data-driven models can be powerful tools, especially when your system involves a lot of different variables which can be difficult to make sense of through simple plots or linear relationships. We can help you make sense of your data and build input-output relationships to help you understand, and control, your system better using statistical and machine learning methods. The main limitation of data-driven models is predicting outcomes beyond the available data range, which can lead to significant uncertainties. Models using fundamental physical laws, offering greater flexibility in forecasting changes to operating conditions and providing deeper insights into system behaviour. At Funis Consulting we also do mathematical, chemical and physical modelling and simulation such as Computational Chemistry, Molecular Dynamics (MD), Reaction Kinetics, Thermodynamics, Computational Fluid Dynamics (CFD), Discrete Event Simulation (DES), Smoothed Particle Hydrodynamics (SPH), Finite Element Analysis (FEA) and Discrete Element Modelling (DEM). From simple chemical reactions to complex physical-chemical processes, we develop custom modelling solutions across industries. Our expertise in equation-based modelling enables us to deliver accurate simulations, helping businesses improve predictive accuracy, optimise processes, and gain a deeper understanding of their operations. Contact us on info@funisconsulting.com for more information and follow us on Linkedin to stay tuned to our insights. What are the benefits of Code Optimisation? With expertise in the latest optimisation techniques, we enhance existing code or develop high-performance solutions from the ground up. We can optimise both CPU and GPU-based code and our software-agnostic approach ensures compatibility with any programming language, allowing seamless integration into your current systems. Whether you're accelerating simulations, optimising machine learning workflows, or improving large-scale data processing, we help you achieve faster, more efficient results. GPUs have revolutionised scientific computing and machine learning, dramatically increasing computational efficiency. When code is optimised effectively, GPU computing can reduce model-building and simulation times from months to minutes, unlocking new levels of performance. Read our article on code optimisation and Follow us on Linkedin for more updates. If you would like further information about how code optimisation can help you contact us. How can Process / Parameter Optimisation help my business? Process / Parameter Optimisation plays a crucial role across industries. If you know the desired outcome but aren’t sure which variables to consider or how to manipulate them, that’s where we step in. Every business generates valuable data, and when leveraged correctly, this data becomes a powerful tool for building models that answer critical questions. Whether you need a simple linear model or advanced techniques like neural networks, we have the expertise to guide you. Let us help you optimise your processes and parameters, using data-driven models to achieve the best possible outcomes, faster and more efficiently. Contact us to discuss further whether Process and Parameter Optimisation can be for you. How does Data Analysis & Visualisation benefit my business? Data is the backbone of any model, whether it’s empirical, data-driven, or based on first-principles physics and chemistry. However, the real value comes from interpreting and applying data correctly. While gathering the right data is essential, it’s how you analyse and visualise it that drives meaningful insights and informed decision-making. At Funis Consulting, we help you navigate the complexities of data analysis and visualisation. We guide businesses in selecting the best methods and tools tailored to their specific needs, ensuring the data collected is relevant, high-quality, and ready for analysis. With our experience across various industries, we make sure the right data is used to build robust, reliable models. Once your data is gathered, it's the interpretation that unlocks its true potential. Raw data alone isn’t enough, it needs to be transformed into clear, compelling insights. In certain cases we use advanced machine learning techniques and AI integration, to ensure that your data is analysed to reveal actionable strategies that drive smarter, data-driven decisions. We create intuitive visualisations that simplify complex datasets, enabling you to communicate insights effectively to stakeholders. With clear, well-structured visualisations, you can confidently present your findings, ensuring transparency, credibility, and a stronger foundation for decision-making. By leveraging the power of data analysis and visualisation, your business can unlock smarter, more strategic decisions, enhancing efficiency and driving innovation. Contact us today to discuss more. How can Food Science & Technology Consultancy help my Company? In the fast-paced and ever-evolving FMCG industry, staying ahead of the competition requires a deep understanding of the science behind food processes and manufacturing. Whether you're formulating a new product, refining an existing one, or exploring innovative food alternatives, a scientific-tech driven approach is key to optimising quality, functionality, and consumer appeal at every stage. At Funis Consulting, we offer the expertise you need to navigate these challenges. With years of experience across a wide range of food and beverage products, from refrigerated items with short shelf lives to sterile products, we help businesses enhance product stability, improve shelf life, and ensure compliance with regulatory standards by building models that help them formulate and/or improve their product. Our modelling expertise spans food chemistry and physics, enabling you to maintain optimal taste, texture, and nutritional value, fundamental factors for safe quality food and beverage products which are successful in a very competitive market. Thanks to modelling and simulation techniques we are able to provide you with precision consultancy in formulation, process optimisation, and packaging solutions, ensuring your product is both innovative, safe and practical. Additionally, it also helps with designing and analysing shelf-life studies to help you develop the right product for your market, all the while ensuring that your product complies with all relevant regulations, including accurate ingredient lists, nutritional information, and compliant claims. With our support, you can confidently bring your product to market without delays, ensuring it’s market-ready and positioned for success. Contact us today to discuss further how food science and technology can help your business. How can I book an appointment with Funis Consulting? Just send us an email on info@funisconsultancy.com or fill in the Contact us form and we will get back to you as soon as we can. I am not very technical, however I would like to understand whether Funis Consulting can help my business. Will I be able to understand the solutions that Funis Consulting is proposing? Funis Consulting provides scientific and technical solutions which are generally complex in nature, however we do our very best to explain things in a manner which is easy to understand from the first meeting, so as to cater for all audiences. Funis Consulting ensures that its solutions are designed with the end-user in mind. All solutions can be made to feel easy to the user, as well as ensuring that such solutions are sustainable and human-centric. Further to this we can provide training and support on-site or online as the situation requires. We have experience with training and teaching people, and so we feel that we are in a position that we can assist stakeholders from all parts of the business. In addition, we speak English, Maltese and Italian fluently. How can I reach you? You can reach us by email on info@funisconsulting.com or by filling in the Contact us form. What fees do you charge? The fees for our services are very much contingent on the project involved. It would be very difficult for us to give you a project cost before we understand the scope of your project. Contact us so that we can understand your needs better. Is it possible to have an on-site first meeting with you? First consultations / meetings held online or on the Maltese islands for the purposes of understanding whether Funis Consulting is for you, are free of charge. If you wish to have a first on-site consultation but you are located abroad, this can be arranged, however it will be against a fee, as this would involve travelling. Contact us to book your meeting with us. Can Models be made to feel easy and user-friendly? Will staff that is not technical be able to use the technology with ease? Funis Consulting ensures that its solutions are sustainable and human-centric. This means that the software, models or technologies are made to feel easy-to-use as we keep the end-user in mind at all times while designing the solution. For example, different outputs may be required by different people, or the same dataset may be displayed differently to cater for different audiences. This is made possible by designing friendly interfaces while complex algorithm-based technologies are running in the background for you. We also provide training sessions for different audiences, as well as support. Training and refresher training is also available, both in person as well as online as the situation requires. Talk to us to find out how our solution can help you, your team and your business grow.

The core services offered by Funis Consulting are Custom Software Development, Process & Parameter Optimisation, Data Analytics & Visualisation, Mathematical, Physical & Chemical Modelling, Code Optimisation & HPC and Machine Learning & AI Integration. We also offer Scientific Consulting for FMCG by building models to assist in new product development to food chemistry insights. Services Modelling & Simulation | ML & AI | Process Optimisation | Code Optimisation | Data Analysis & Visualisation | Food Science Modelling & Simulation Mathematical, Chemical and Physical Modelling and Simulation Data models can be a very powerful tool in your arsenal however at times they can only get you so far. Using data models to predict what will happen far outside the range of your data can be very difficult to do, often leading to significant uncertainties. Having said that, most processes can be modelled using the fundamental laws of physics, thus giving you greater flexibility in predicting what will happen if you change your operating conditions and/or help you understand your process much better, therefore providing deeper insights into how systems behave under different conditions. Whether it is data-driven modelling and simulation such as statistics and machine learning, or First-principle / Physics-Based Models, such as Computational Chemistry, Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and Discrete Element Modelling (DEM) we have got you covered. We can help you build a model for the simplest of chemical reactions to the most complex physico-chemical process, regardless of the industry you work in. With expertise in equation-based modelling for physical and chemical phenomena we work to develop solutions tailored to your needs. Leveraging on advanced modelling techniques, we help businesses enhance predictive accuracy, optimising processes and gaining a clearer understanding of their operations. Advanced Machine Learning & AI Integrating First-Principles Models with Machine Learning Why settle for just one approach when you can combine the best of both worlds? By integrating machine learning with first-principles models, you can unlock more accurate predictions and optimised outcomes. Whether it’s coupling machine learning with physical models to improve their accuracy, or using AI to fine-tune and optimise your models, we have experience with both approaches. Using the latest techniques in parameter estimation and surrogate model building, we can enhance the predictive power of your models. With machine learning’s ability to analyse large datasets and identify patterns, combined with the robustness of first-principles models, we ensure that your model is as precise and effective as possible. This integration allows for faster, more reliable decision-making, helping your business stay ahead in a data-driven world. Process & Parameter Optimisation Data Model Building and Trial Planning for Optimisation Optimisation can be used across all industries, whether you are looking to build accurate forecasts, optimise your manufacturing process, or predict the impact of changes to your settings. If you know the goal, i.e. what you would like to achieve, but you’re not sure which variables to use and how in order to achieve that goal, that is where we come in to help you out. Every company generates data and when good data is used and leveraged effectively, it can be used to build powerful models that answer these key questions. Whether you need a simple linear model or more advanced techniques like neural networks and machine learning, we’ve got the expertise to support you. Code Optimisation Enhancing the Power of Scientific Computing with Code Optimisation and GPU Computing With the massive boost in computational efficiency provided by GPUs, it is no wonder everyone is getting on the bandwagon for scientific computing and machine learning model training. If optimised properly, using GPUs can help cut own your model-building and simulation time from months to minutes. With our expertise in leveraging the latest technology we can optimise your existing code or develop new solutions from scratch, helping you can achieve the desired results and as quickly as possible. In addition, we are software agnostic, meaning we can work with any programming language, ensuring a seamless integration into your existing systems. Data Gathering, Analysis & Visualisation Unlocking the Value of your Data No matter the type of model – whether empirical, data-driven, or based on first-principles physics and chemistry – data is essential for building and validating the model. The quantity of data required varies depending on the model, but obtaining the right data is often the biggest challenge. We can help you design the most efficient data collection strategy, ensuring you gather the right data, to ensure good data is available and to determine the optimal number of trials needed to build a robust model. Not sure what data you need or how to collect it? Don’t worry. With our extensive experience across various industries, we can guide you on the best equipment to use and how to effectively collect the data for your specific needs. However, data on its own does not mean much unless it is properly interpreted. Nothing beats the right visualisation methods to help transform raw data into compelling stories, which will guide the business in informed decision-making. Whatever the size of your datasets we can provide data analysis and visualisation. Whether your dataset is vast, meaning data collected over a longer period of time; or just a snapshot of the current scenario, we will help you make sense of it all. Here at Funis Consulting, we will analyse your data and create clear, intuitive visualisations that not only make the data easier to read and understand, but also empowers you to communicate insights effectively to stakeholders, ensuring your explanations are clear, and the data behind the business decision is both sound and convincing. So, let us help you unlock the full potential of your data, turning it into a powerful tool for smarter, more strategic decision-making. Food Science Consultancy From New Product Development to In-Depth Food Science Insights The FMCG industry is a fast-paced, dynamic one, with new products being constantly launched all the time, and consumer trends evolving rapidly. Whether you want to develop a new product from scratch or update an existing one to meet changing demands or regulatory standards, we can provide you with the scientific expertise to meet your business needs by building models that will help you achieve your goal. Whether it is refrigerated products with a short shelf life, or sterile products, we have extensive experience working with a variety of food and beverage products. Having developed multiple products which were successfully placed on the market over the years, Funis Consulting is able to provide model-based consultancy services covering formulation, process optimisation and packaging solutions to ensure your product is innovative, safe, high-quality, successful and practical. Furthermore, through the use of modelling and simulation we can support you in designing shelf-life studies and analyse the resulting data to help you develop the right product for your market.

Funis Consulting bridges science and innovation through scientific computing, such as computational chemistry and physics, advanced modelling & simulation, process optimisation and data science. We help organisations understand complex systems, optimise performance and make confident, insight-driven decisions. Data Handling Scientific & Technical Services Food Scientific Consultancy About Us Funis Consulting Ltd is a dynamic company based on the Maltese islands (European Union) and was founded by Robert Cordina who brings over 20 years of experience working with startups, multinational corporations, and academia. Driven by a passion for science, technology, and innovation, Funis Consulting specialises in custom modelling and simulation software development to provide businesses with precise consulting services as well as applications and tools for a wide range of industries, enabling such businesses in their decision-making, innovation, performance, competitiveness and efficiency. The first key area is Modelling and Simulation, encompassing both data-driven approaches and first-principles/physics-based methods. Our expertise spans machine learning, mathematical, chemical and physical modelling, process/parameter optimisation, and high-performance computing, allowing us to tackle complex challenges with precision and efficiency, using both custom and off-the-shelf software. Whether it’s data-driven modelling – such as data analysis, statistics, advanced machine learning, and AI – or physics-based approaches like chemistry models (reaction kinetics, Molecular Dynamics (MD) and thermodynamics), Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), Smoothed Particle Hydrodynamics (SPH), Discrete Element Modelling (DEM) or Discrete Event Simulation (DES), Funis Consulting develops and integrates bespoke software and modelling solutions using your software/programming language of choice to enhance decision-making, automate processes and optimise business operations which drives efficiency, innovation, and create real-world impact. Whether through advanced simulation techniques, machine learning integration, or GPU-accelerated computing, we help businesses remain at the cutting edge of innovation. The second specialisation is scientific consultancy for the FMCG industry through the use of modelling and simulation. With a strong background in chemistry and physics, we support businesses in key areas such as research and development, product renovation and innovation, product formulation, NPD and chemistry insight, ensuring your business stays ahead in a rapidly evolving industry. Our Core Specialities are: Build and integrate smart, custom software, from scientific applications to business tools GPU & High-Performance Computing (HPC) Scientific Computing and Mathematical, Physical and Chemical Modelling & Simulation Process / Parameter Optimisation through the use of models Code Optimisation (we are software agnostic for a seamless integration into your current systems) Making sense of complex data through Data Analytics & Visualisation tools / methods Advanced Machine Learning and AI integration in certain models Model-based Scientific Consulting specialising in FMCG and Food Manufacturing industries ranging from new product development to chemistry insights We offer flexible project structures tailored to businesses of all sizes, whether large or small. Our approach can be fixed-cost or time-based, depending on your projects’ needs. Plus, our first online consultation/meeting to see how Funis Consulting can help, is always free, with no obligation. Send us a message to discuss more about your project, by clicking here . Check out our FAQs and Services sections to know more about what we do. Follow our Blog for our insights into the world of Scientific Computing and Scientific Consultancy. Services At Funis Consulting Ltd, we offer a range of services across different industries, to help businesses stay at the forefront of innovation, efficiency and excellence. Through our modelling and simulation, as well as process optimisation services we tackle complex challenges using both custom and off-the-shelf software, depending on your needs. Whether it’s leveraging data-driven models or physics-based simulations, here at Funis Consulting Ltd we deliver the precision and reliability that your Company is after in order to stay ahead in the ever evolving landscape of innovation. Read More About Our Services Bringing Science, Technology and Innovation together Beyond the Numbers: Gaining Insights Through Data Analysis and Visualisation Collecting data is essential, but its true value lies in the ability to interpret and apply it effectively. Businesses must make sense of the data they gather to drive meaningful insights and informed decision-making. With the right analysis and interpretation tools , companies can transform raw data into actionable strategies. By leveraging advanced machine learning techniques and AI integrations, businesses can unlock smarter, data-driven decisions that enhance efficiency and innovation. Read More About Our Services Food Science Unlocked: Expert Consultancy for Smarter Solutions A strong understanding of the science behind food processes and manufacturing is key to developing successful products and staying competitive in an ever-evolving industry. Whether it’s creating a new formulation, refining an existing product, or exploring innovative food alternatives, a scientific-tech science-driven approach ensures that every step is optimised for quality, functionality, and consumer appeal. By applying the use of modelling and simulation tools coupled with expertise in food chemistry and physics, we help businesses can enhance product stability, improve shelf life, and meet regulatory requirements while delivering on taste, texture, and nutritional value. With the right scientific insight and technology, your company can navigate challenges more effectively and bring groundbreaking food innovations to market with confidence. Read More About Our Services Past and Present Clients and Partners Mdlz quote Vow_quote Mdlz quote 1/2