Your Digital Twin from an AI Mother

It’s no secret that industrial automation improves process efficiency with Digital Twinning and Artificial Intelligence (AI) being the two most notable emerging trends. Near-future expert forecasts predict a radical and permanent shift in product design and development. In its course, it will be up to the most innovative manufacturers to take advantage and benefit from the new product-centred technology.

 

Does the concept of digital twinning seem too far-fetched to be applicable for small- or medium-sized enterprises (SMEs)? Not really, but oftentimes it seems so. Yet, such businesses are the backbone of the UK economy, so innovative digital helpers, like IndustriGen are quickly filling the niche in supporting them throughout the entire digital transformation process with affordable software solutions. A challenging but truly rewarding endeavor. 

What is a Digital Twin: Lifting the Curtains 

Whenever there is a new trendy topic, we have to think about how it contributes to the world we live in. In the increasingly digitised communities, we live and work in, the challenge to adapt to new market conditions is present. However, digital twins are not entirely new. The concept dates back from 2002 when prof. Michael Grieves discussed the information mirroring model as part of product lifecycle management and postulated that each physical system also consists of virtual components. Later, NASA officially named the prototype concept “digital twin” while attempting to build a virtual system to control physical ones in outer space. 

A digital twin is a real-time digital copy of physical products that helps manufacturers analyse product features, boost future performance and achieve continuous improvement. Digital twinning comes to aid those businesses that are closely intertwined with digital product development, monitoring & predictive maintenance. The true abundance of this technology lies in its vast use cases applied to manufacturing as entire processes gradually become dependent on modern technologies due to accelerated digital transformations. While decades ago, mechatronic systems used to be the gold standard of manufacturing, nowadays Industry 4.0 leads us to new generations of cyber-physical systems with machine-to-machine communication and integrated cloud services. 

Who Uses Digital Twins and Should You too?

If you’ve read this far, perhaps you ask yourself what industries can benefit from a digital twin and whether yours is among them. Some major manufacturing industries that already utilise this technology are the automotive, food and beverage industries, aerospace engineering, metal processing etc. New research by Gartner revealed that 31% of surveyed companies adopted a digital twin as an additional Covid-provoked safety measure, allowing remote asset monitoring, while another 27% plan on using this technology autonomously. Think of a digital twin as a virtual data container of products or complex processes such as product design, quality inspection, packaging and performance optimisations – all at your disposal wherever you need it. 

In today’s dynamic manufacturing arena having a digital twin means your factory is fully equipped with a mighty assistant in vital areas such as diagnostics, analytics and predictions. Among the many use cases applied to manufacturing is that digital twins provide you with timely performance reviews, an invaluable asset in production. Such reviews simultaneously help cut down manufacturing costs and act as a meaningful step in the decision-making process of production managers and process engineers. 

New Emerging Market to Nourish Development 

A digital twin can perform insightful simulations from various vantage points and deliver essential information of what’s available and what’s possible. All these lead to deeper product understanding and leaves the doors of optimisation opportunities wide open. This unique tool for virtual representation enables smooth information flow unlocking the full potential of entire manufacturing value chains. Running what-if scenarios boosted by AI capabilities can unfold previously unknown product utilisations.

Product development is inevitably dependent on in-depth market analysis and competition research. Alan Prior, a EuroNorth VP at Dassault Systèmes gives the example of airplanes and deodorants – the latter is quicker to design and run prototype tests on. However, when it comes to producing exceptionally large product quantities, it is essential to fully grasp the manufacturing process to shorten time to market, reduce risks and encourage sustainable production. With a digital twin on your side, you effortlessly run simulations and adapt to changing demands prior to actually implementing product modifications. Not only does this save you valuable time and financial resources in the long run, but you also serve your brand customers better.  

While exploring prospective innovative technologies, decision-makers should concentrate on strategic long-term tech solutions that contribute to digital infrastructure. On the verge of Industry 4.0, digital twinning may as well turn out to be one of the best coping strategies for manufacturers to 2020’s powerful adaptation lesson. In case you don’t feel like walking on the untrodden ground anymore, we invite you to apply for our accelerator programme for UK manufacturers, starting in September. Application is open, hurry up as only selected manufacturers will have the opportunity to hear out our industry leaders.

 

Author Biography Aleksandrina Vasileva 

Aleksandrina is a Content Creator at Dreamix, a custom software development company, and is keen оn innovative technological solutions with a positive impact on our world. Her teaching background, mixed with interests in psychology, drives her to share knowledge. She is an avid reader and an enthusiastic blogger, always looking for the next inspiration.  

 

Top Digitalisation Practices for Manufacturing Quality Control

We’re lucky to live in the most abundant time in history and to work in dynamic industries that continuously innovate. Digital transformation in manufacturing is a rising trend, sweeping up old practices and establishing new and powerful ones with the help of digital technologies such as Artificial Intelligence (AI) and its subtype Machine Learning (ML). If you think about it, the way you perceive change is not related to the trend itself but it has a lot more to do with your preparedness for it. It’s automation o’clock all around the world, so will you stay still or move your clock forward? 

 

The lack of a cohesive long-term innovation strategy and hesitations about digitalisation are among the biggest obstacles towards embracing Industry 4.0 revolution. As with any hot trend out there, lots of misconceptions around AI-powered automation circulate online, demotivating small and medium-sized enterprises (SME) to optimise their manufacturing process and gain momentum when they need it the most. In the UK, a number of tech startups help manufacturers get a fresh perspective on the affordability and scalability of building intelligence solutions for manufacturing. One such instance is the collaboration of IndustriGen with the University of Manchester, MAKE UK, The Blair Project, etc. with a focus on available use cases for SMEs. 

 

Avert or Welcome New Challenges?

As the Covid-19 pandemic struck and the Brexit aftermath became evident, lots of business blind spots emerged from the massive economic uncertainty and market insecurity. The UK’s Office for National Statistics recently revealed an unsettling decline in the capital used in manufacturing production, dropping to 8,8% in 2020 – the lowest since 2010. It seems like the only reasonable option for SME manufacturers is to welcome the winds of change and get ready.

 

In fact, 2021 MAKE UK’s executive survey pinpoints that digital technologies and innovative software tools were essential components that glued together business continuity and remote work throughout the pandemic waves. Having learned their post-pandemic lessons, 42% of the manufacturers now seek new opportunities to invest in green technologies, bringing them process efficiency and lowering their environmental impact and energy costs. Emerging concerns around new potential lockdowns, high bureaucracy costs and technical skill gaps also urge manufacturing SMEs to equip their daily operations with business resilience.

Automated Quality Control 

Each manufacturing facility involves a process of Quality Control (QC) for examining and analysing the products and their features to make sure they are fit for the customer’s needs and comply with the company’s quality standard policies. However, the disrupting Industry 4.0 is getting hard to contain, and it can get expensive for SMEs to fully engage human specialists during the step-by-step QC process. Manufacturing is traditionally based on four key elements: Quality, Dependability, Flexibility and Costs and according to the famous Sand Cone Model, attention and resources should firstly be directed to quality and then all else as quality management reflects on cost efficiency in the long term. 

 

Thankfully, we live in the golden age of digital revolution and AI can successfully help small and medium manufacturers survive and thrive in the approaching Fourth industrial revolution, lowering both technical and manpower costs. According to a Delloite report, companies are now starting to grasp the full scope of the massive digital transformations that take place as you read these lines and seek options to further automate their existing manufacturing processes. Chances are that, in the long run, later adopters simply won’t be able to keep up with niche competitors and will risk being marginalised or start losing clients.

 

When AI Steps in, Product Quality Blossoms

Artificial intelligence tends to befuddle people. After all, the perpetual struggle to create new work positions for employees in an overpopulated world now seems illogical when intelligent AI systems slowly take over. No such thing. In fact, AI promises to create more additional positions for manufacturing staff to shine, simplifying existing tedious jobs, as described in a Delloite report. For innovative manufacturers, leveraging digital transformations means they’ll have to design new jobs in the manufacturing sector such as predictive supply network analyst, digital twin engineer or smart factory manager. 

 

But before all this can turn into reality, smart integratable software tools like DCS (Data Collection System), IPQS (In Process Quality Control System), EQMS (Enterprise Quality Management System) and MES (Manufacturing Execution System) will have to enter the game. For instance, a DCS gathers all relevant process data such as material handling, data entries, activity and performance logs to create visual reports on process outcomes, making paper documents redundant. Then, it communicates with a visual control quality inspection programmed with ML algorithms to detect defects on the assembly line and remove them before final packaging and dispatch. Functions like real-time monitoring & diagnostics through computer vision can assist predictive maintenance, boosting quality control and generating remaining useful life estimations of machines. 

 

It’s Officially Automation O’clock

The main purpose of innovation has always been to improve current processes, boost productivity at a lower cost and bring more business value. The opportunities of Industry 4.0 when it comes to new Quality 4.0 practices around technologies such as Big Data, AI and ML, Cyber-Physical Systems or Visual Inspection are immense. In fact, their implementation is the digital milestone before reaching new business heights for small and medium-sized manufacturers. New digital software solutions flow into your factory’s Deming cycle (Plan, Do, Check, Act) and help you optimise quality inspection processes while saving you time and money.

 

What’s even better is that recent political initiatives, such as the super-deduction tax incentive leads businesses towards innovating more than ever now as it was designed for repositioning UK businesses as international competitors. Recent political initiatives, such as the super-deduction tax incentive, aim at boosting innovation more than ever now as it is designed to reposition UK businesses as international competitors. A sneak peek into the budget’s factsheet reveals that companies can claim temporary 130% capital allowances on qualifying plant and machinery investments such as computer equipment, computer software etc. The key criteria are that expenditure contracts must date from 3 March 2021 and incurred between 1 April 2021 and 31 March 2023. The strategy creates a time-sensitive period to accelerate digital transformation among all manufacturing facilities. It’s time for executive discussions as the clock is literally ticking.

 

Author Biography Aleksandrina Vasileva 

 

Aleksandrina is a Content Creator at Dreamix, a custom software development company, and is keen оn innovative technological solutions with a positive impact on our world. Her teaching background, mixed with interests in psychology, drives her to share knowledge. She is an avid reader and an enthusiastic blogger, always looking for the next inspiration.  

 

Industry 4.0: How to Survive It and Thrive

Industry 4.0: How to Survive It and Thrive

We live in the golden age of innovation. Recent advances in digital technology make it possible for small-to-medium enterprises (SMEs) to further automate their manufacturing processes. The best news is that it’s no longer a choice between cutting your production costs or improving your product quality – with the right partner you can do both at the same time. While the task of process automation has traditionally been a major challenge, new innovative software products make it easier and more affordable than ever before.

 

Navigating their way through all pandemic restrictions and post-Brexit effects has not been easy for SME manufacturers. The quest to help them survive the digital upheaval and thrive on a budget has led startups like IndustriGen to develop affordable automation software designed for manufacturing needs such as data collection systems for next-level visual reports, computer vision for optimal quality control or digital twins for ultimate product simulations.

What is Industry 4.0? 

Automation is changing the face of manufacturing. Industry 4.0 or the Fourth Industrial Revolution will have a huge impact on traditional manufacturing processes. SMEs that want to remain intact from the ongoing digital transformation and stand out from their competitors will eventually have to embrace new technological solutions. Emerging trends such as sustainability, innovation and data analytics are no longer just business buzzwords but real phenomena, taking place as you read this. What better time to future-proof your processes and skyrocket your business than now? 

 

As you know, one of the key value drivers in the digital age is automation. Designed to improve existing processes, limit waste and reduce operating costs, Artificial Intelligence (AI) can help manufacturers make a smooth transition to the new business environment and comply with the high standards regarding low environmental impact. Just imagine how much energy, human and financial resources are currently being wasted around the world with paper documents and reports! The best news is that despite being a setback, Covid-19 also opened the doors to innovation and new investments as it accelerated long-postponed digital transformations across manufacturing industries.  

Automated Processes with a Seamless MES

To reap the benefits of digitalisation, many manufacturers turn to innovative multi-talented solutions to help them re-invent process efficiency and reduce unnecessary costs in the long turn. Manufacturing Execution Systems are a good initial step for implementing industrial automation software within a manufacturing facility. In fact, international experts predict a 30% productivity boost by 2025 thanks to Industry 4.0 related innovations. 

 

MES can be a key component of your successful digitalisation strategy. As a technical system, MES operates at the process-related level and plays an integral part in production management as it is responsible for real-time production control. What an MES does is collect data from manufacturing processes, helps production engineers identify errors and optimise the process to save costs and increase productivity. 

 

What can be automated with a MES and How? 

 

For example, let’s take a closer look at the food processing industry. The Covid-19 crisis once again highlighted the importance of this industry. Food processing faces extraordinary challenges because of the current dynamic nature of market demands. For manufacturers who maintain wider product lines, the challenge is even greater. Especially in the UK context, the pressure for an optimal production process is very high due to low end-product prices, increased quality demands and rising energy costs. 

 

So how can a system like MES help you automate processes as a manufacturer? Essentially, every manufacturing business produces tons of data streams alongside its usual product line. In the era of digitalisation, more and more factories opt for interconnected machines that generate massive amounts of production-related data. However, this is the easy part and the more crucial aspect is how you extract meaning from this data collection. A robust MES product can be a powerful asset when you need to optimise individual machine behaviour or attain higher performance between multiple production modules. 

 

It is a privilege to live and work in an era of abundant technological innovation and real-time analytics. With today’s advanced technology such as Artificial Intelligence (AI) and Machine Learning (ML) algorithms, manufacturers can solve previously unsolvable challenges. While complex calculations run in the background, the MES visualises automated Drag and Drop reports on ongoing primary processes (e.g. sterilisation, drying, freezing and packaging), advanced performance predictions & efficient energy management. As a result, with the implementation of just one MES solution, you eliminate paper documents, optimise process monitoring and get enhanced workflow. 

Elaborate Automation ≠ Expensive Software 

What comes to mind when you hear manufacturing automation? The traditional way of thinking suggests long and expensive implementation timeframes. However, as it turns out, there is a smart way to design affordable powerful AI software. Affordability is also a fortunate byproduct of the combined expertise of technical talent and domain knowledge. Digital transformation is all about facilitating meaningful data insights and enabling people to collaborate efficiently and get the most of processes. 

 

Leveraging the success stories of tech giants like Google and Amazon, the software development for a comprehensive AI-driven system applied to manufacturing becomes simpler and cheaper than expected. The reason is that ML algorithms use Deep Learning methods and Neural Networks to analyse and make sense of the incoming data. With most of the AI algorithms already available as open-source code, only the upper layers of the programme, providing it with special criteria and parameters to work with.  

Future-Fit Manufacturing On Demand 

Modernisation consists of consistent efforts towards process optimisation. Many UK manufacturers embrace the philosophy of continuous improvement (CI) and invest in employee training just to find out that something’s still missing. A common reason that impedes CI is the lack of timely communication of suitable Key Performance Indicators (KPIs) and end-goals for the workers. The usual scenario includes a visual board on sales, productivity, sick leaves etc. on a monthly basis which is a long period. The most efficient way to get relevant daily statistics & shift reports and involve more senior employees in important decision making is to trust the MES-delivered data.

 

The core idea of next-generation IT solutions in manufacturing is to simplify and improve existing processes, remove redundant steps and future-proof business models. Linking MES to your unique KPIs provides you with the opportunity to innovate existing processes and make them flexible and adaptive to constantly changing market conditions, including better product quality, process sustainability and shorter supply chains that cut down transportation costs and risks. 

 

Author Biography Aleksandrina Vasileva 

Aleksandrina is a Content Creator at Dreamix, a custom software development company, and is keen оn innovative technological solutions with a positive impact on our world. Her teaching background, mixed with interests in psychology, drives her to share knowledge. She is an avid reader and an enthusiastic blogger, always looking for the next inspiration.