The powerful twin you never had

I started my career working for Rolls-Royce plc where I became a chartered Engineer. I then moved into FMCG consultancy where I developed my understanding of the FMCG industry and it’s unique complexities. It was actually from the Rolls-Royce days where I developed my passion for technology within manufacturing. The systems, processes and software used to manage Jet Engines through production and their life-cycle offered an in-depth understanding of production and product performance, critical to the success for the company.

Since joining FMCG I continue to be passionate about the future of manufacturing in Australia, and how technology will underpin improvement and ultimately success in a challenging marketplace. I now find myself leading Pollen Technology, where our ethos is to find applicable value-added solutions today, which will optimise businesses and ensure the journey towards being relevant tomorrow.

The challenge is no longer about being able to measure and access data – the challenge for organisations tomorrow is how to identify the information required to support optimal decision making.  Advances in data availability mean that we must be smarter in using it to our benefit, advances in computing power mean we can do this cost effectively. We believe there are 2 key technologies of today, Live Decision Analytics and Digital Twins, that will transform supply chains.

You mentioned the fact that digital twins will transform supply chains, can you elaborate?

Studies have shown that human computing power using more than 4 variables is only as accurate as chance, yet in many businesses today we leave complex, multivariable decisions to excel and a human. The problem with this is that we cannot accurately represent real world complexity. Digital twin models within some software packages use stochastic modelling, essentially allowing performance of all elements of the model to perform based on probability, the reason this is so powerful is that it will accurately predict scenarios where specific events overlay to cause poor performance. A digital twin will not only model scenarios but will determine the risk to meet it.

A tool this powerful can unlock significant benefit within your supply chain and can be used as a tool in many different forms, depending on the level of adoption. In its most basic form a digital twin model can be used to improve decision making capability within a business to test scenarios, for example instantly identifying the optimum production sequence following a critical failure to protect customer service or cost. Using actual performance data it will consider the full complexity of your factory or supply chain to determine the optimum solution to meet desired outcome. This could offer benefit in product costings, both present and future, not only accurately determining the cost of the new product, how it should be scheduled, but mapping the impact to other products, commonly missing during NPD. One could use a digital twin to maximise capital investments, see how changes in suppliers, customers or even other sites affect the overall network before agreeing to these changes. This allows businesses to gain confidence in security of supply through ‘what if’ analysis.

To unlock the true capability of a digital twin a business should integrate its power into their planning cycle. Use the twin to schedule and sequence production throughout the supply chain. A digital twin is designed to complement existing supply chain software, Transactional systems such as SAP are critical to financial reporting, Operational systems like MES are embedded and link the factory floor, a digital twin compliments both systems by creating a critical link between the two, more often than not occupied by Excel. When effectively employed a digital twin can align and optimise multiple schedules inclusive of underlying variation, adding optimisation and risk analysis to compare and schedule feasible solutions. It can offer real time allocation and rescheduling of shared resources across the entire value chain (e.g. labor, machines, tooling, jigs, forklifts, AGVs, etc.), rescheduling of a complex, multi facility value chain inclusive of multiple distribution networks with all real world variability and constraints, in mere minute.

In essence a digital twin will increase responsiveness to a fluid operational environment to deliver services on time and within budget, by taking all real world variability and current challenges into account.

 

It sounds interesting, but why now? Hasn’t this type of product been around before? What has changed to make this more accessible today?

True, there has been simulation software available for over 30 years, software such as Arena or Tempo have been offering a level of simulation for decades. The key difference today is the simplicity of the solutions available today. Where companies like McLaren Applied Technologies are developing bespoke digital twin software, off-the-shelf software packages such as Simio are so versatile and adaptable they can be used for all supply chain modelling.

What this essentially means, is you do not need to have a team of programmers to create and maintain a digital twin. Available software uses simple object-based modelling which can be tailored at all levels of complexity to accurately represent the most complex supply chain. The beauty of using object-based modelling, is once you have built a model, let’s say of a factory, this model can be imported into your network model as an object. Thus, adding complexity to an already built model will just build upon that complete, it does not require a whole new model to be created.

Businesses are becoming increasingly data rich. The difficulty today is being able to use this data to add value. As a digital twin offers easy integration to existing software and can be linked to live information, it will be a critical tool to ensuring businesses consider and appreciate the complexity that exists in their businesses.

Complexity in manufacturing is increasing, marketing teams are pushing higher diversity of SKUs, more changeovers, faster more effective NPD, less risky capital solutions. This will not change, in fact it will only become more prevalent, successful businesses will embrace this by employing the right tools to embrace complexity.

 

So how do I go about this in my business? How can I do this?

When considering technology within your supply chain it is worth remembering the philosophy in the Tech world of startups, think big (what is your vision), start small (complete small trials to prove concept, do not get bogged down in trying to solve the world) and fail fast (identifying that something does not work can be just as valuable as the opposite).

With that said, as with any technology, it is critical that before implementing a digital twin you must consider the people and the process. Who in the organization will use the digital twin and for what purpose, once understood it is important to then identify any changes to process which will be needed to allow effective use of the digital twin.

In making the model, however it is critical to understand the level of complexity needed in your model. What inputs do you have, what is the end use of the model, what are your requirements? At Pollen we are passionate about unlocking potential in supply chains, we have extensive experience determining how to determine the right input with the right level of complexity. Over complicating your model will result in longer creation time, oversimplifying will detract from the value of the output.

In order to gain traction, validate value to your business and ensure a digital twin is sustainable within an organization we would recommend generating a proof of concept model to solve a specific issue. The model will add value and can be used afterwards, the benefit is that it can build tangible business case for increasing the use within the business with very little risk.

At Pollen we have a team who can rapidly build a model of your supply chain or factory, train your team to become Digital Architects, and build processes and capability within people to ensure ongoing sustainability and success.

Oliver North – Head of Technology at Pollen Consulting Group