Myths about Digital Transformation/Manufacturing.

What is a myth, but a traditional narrative that catches people’s imaginations and soothes their sentiments! The stories get told with much conviction, with minimal or no corroborative proof, and soon become a widespread belief. Business myths are misconceptions arising from the assumptions made by ill-informed minds. Mythological tales can be very entertaining and form a part of a rich culture. Business myths might not serve any purpose and can be misleading, discouraging, and detrimental to company culture, too. If only we were to read between the lines, we would discover truths. 

Ever since tales of the Industry 4.0 became rife, innumerable ideas — true and false — regarding the digital transformation of manufacturing have started doing the rounds.  

Here are some myths we thought needed busting so that you can make informed decisions based on facts: 

Myth #1: Digital transformation is a big-budget affair, therefore, not meant for small companies.  


The first thought that comes to mind when discussing digital transformation is the costs involved. As nothing comes for free, digitalization comes at a cost, but strategically planning an AI adoption strategy will not drill a hole in your pocket. On the contrary, the resultant business benefits in terms of ROI will outweigh all expenses. Phasing out the transition could also help SMEs streamline their processes and enjoy profits. Industrialists have been reinvesting their gains into leveling up on the digital platform. AI applications for manufacturing optimization are accessible and affordable by all.  

Myth #2: AI is a disruptive technology that will remove the ‘man’ from the equation in manufacturing.  


All of the previous industrial revolutions since the late 17th century changed our life drastically.  History stands as proof that technological development has only created more jobs and better opportunities for humans to progress. AI is yet another technology designed to enable human capabilities and not cripple society. With AI assistance, humans can increase productivity by completing job tasks faster with precision accuracy, making businesses profitable. That will also leave more scope for skilled workers to get employed in more meaningful roles.  

Myth #3: The outcome of Smart Manufacturing is not measurable in tangible values. The benefits are not immediate.  


 For an average USD 5 billion company with a 10% margin, investments in digital technologies produce an additional USD 425 million in profit. Of all surveyed industrialists, more than 60% have stated that digital transformation can help organizations address the business objectives of prime importance — reducing operational costs and growing market share organically. [1] 

Neewee’s own ready-to-deploy AI apps can be integrated with any IoT platform to streamline the manufacturing process end to end, deliver higher ROI and improve product quality within six to eight weeks of implementation. We do this by creating Process Digital Twins that connect and mirror the manufacturing life cycle, revealing cause-and-effect relationships between components, raw materials, and processes. The apps then provide predictions and actionable recommendations using Machine Learning and AI.  

  • Improving process yield by 8-10% 
  • Enhanced product quality by 10-12% 
  • Reduced working capital by 8-10% 
  • Cut maintenance costs by 15-20% 

Myth #4: You can take your own sweet time to digitalize your manufacturing processes. Also, it’s optional!  


The general tendency is to wait and watch how the early adopters of technology are faring with the new intelligent manufacturing methods. However, sitting on the fence is not a healthy strategy if you wish to stay relevant in the rapidly increasing competition. A digitally connected lean manufacturing eliminates wastage, reduces batch-cycle times, and repeatedly delivers consistent quality and throughput. This directly translates as increased customer satisfaction. While traditional ‘unintelligent’ linear manufacturing systems will continue to struggle with delivering on promises, which can end up putting off the customers. Modernization of manufacturing is no longer an option but an imperative for business growth. 

Harvard Business Review sums up: “By the time a late adopter has done all the necessary preparation, earlier adopters will have taken considerable market share; they’ll be able to operate at substantially lower costs with better performance. In short, the winners may take all and late adopters may never catch up.” [2] 

Myth #5: For successful AI adoption in manufacturing, you need to digitalize the entire factory in one go! 


Big Data Analytics, Industrial Internet of Things, Machine Learning (ML), and Artificial Intelligence (AI) apps are different aspects that work together to turn your business operations toward Smart Manufacturing. Each involves cost and complexities. It is neither advisable nor practical to digitize the entire facility in one go. AI applications implementation into the system, working with integrated data analytics, is a step-by-step process involving reiterations to arrive at the best fit for optimizing different production processes. Since there can never be a one-formula-fits-all solution, only a well-developed strategy for AI Adoption guarantees astonishing results.   

It is not debatable anymore, manufacturers can optimize their business to achieve agility, efficiency, quality, and sustainability with AI Applications.  

Final Takeaway: 

The hype cycle about digital transformation of manufacturing carried many myths and even more facts. We have debunked some myths that might be keeping many from taking timely decisions for a digital strategy. It is therefore essential to confirm the credibility of the source before you believe the bit of news. Taking decisions based on myths would be like that notorious game of Chinese Whispers. You run the risk of falling for inaccurately transmitted gossip. 

How to get a 3x productivity boost using Lean Manufacturing with AI

Does the philosophy of Lean Manufacturing with AI have actionable meaning? Simply put, Lean Manufacturing is a management philosophy that urges you toward eliminating waste and improving productivity. It is a legitimate methodology for manufacturers and business owners to adopt, which will help them optimize production, give value to customers, and thus transform into market leaders. But, what is a manufacturer really expected to do to join the burgeoning crowd in Lean Thinking? 

Even Henry Ford, regarded as the Father of Lean Manufacturing, inadvertently created waste in his ambitious attempts at minimizing it. At the Highland Park manufacturing plant in the early 20th century, they tightly monitored the production line of the Model T automobile. The process ‘flow’, from raw material being sourced to the point of sales of the automobile, got planned to the T. (Pun intended!) Although high production standards got achieved and maintained, flexibility in the processes was zilch! There was no scope for variations or any modifications. Also, Ford failed to consider consumer demand and kept pushing finished automobiles into the market. What could one expect from the large pile-up of cars pending sales? He had eliminated operational inefficiencies, but the unsold inventory was another form of waste and monetary loss.  

Offloading the costs incurred by wasteful production processes onto the customers is a big no-no! On the contrary, customer satisfaction is at the core of Lean Manufacturing. Not giving customers value for money will only damage your business relationships. For retaining position between tough competition, production must be flexible and adaptable to customer demands. So how can a manufacturer pull off this feat, improve production efficiency while also reducing wastage and being sensitive to consumer expectations? 

There are a few ways to boost productivity triple-fold (3X) with Lean Manufacturing, and it begins with just one step — embracing Artificial Intelligence (AI). Manufacturing gets Lean when AI breaks down siloed data and facilitates transparent coordination between diverse production teams. AI applications can help manufacturers streamline processes, eliminate waste, and achieve the ultimate goal — customer satisfaction. 

How it gets done — 

  1. Reducing batch cycle time: Manufacturers have to fulfill orders within tight deadlines. Any delay in fulfilling orders can cause huge losses for manufacturers, so being ahead of the game is critical. Bodhee® Golden Production Run AI app helps you identify quality parameters impacting batch performance through real-time visibility of patterns created by the Golden Digital Thread. Experience quality improvement by 10-12% and reduction of batch cycle time by 1-2 %. 
  1. Increasing workforce productivity: Lean thinking with AI brings a radical change in company culture with improved workforce management. Bodhee® Production Performance Monitoring app helps monitor production and Key Performance Metrics such as Overall Labor Effectiveness (OLE) with just one click. It gives manufacturers a competitive edge by reducing errors and requirements for reworking by 15%. It optimizes warehouse operations and improves product delivery time by 8-10%. 
  2. Increasing capacity utilization: It is essential to have dynamic planning in response to the events on the factory shop floors or in the supply chain or user feedback that keeps the businesses agile. Bodhee®Integrated Micro Scheduling AI app facilitates synchronized and Live micro-planning of the entire production process. Manufacturers can work out every tiny detail and customize it, thus ensuring shorter lead times, quality improvement, tailored solutions, and many other desired production goals. 

Studies suggest that 80% of manufacturers who adopted AI over the past two years realized a value increase between a moderate 23% and a significant 57%. Many of them who had latent IT and OT data assets harvested data from IoT sensors, which AI then leveraged to optimize processes and business results (1).   

As the manufacturing industry evolves with the Industrial revolution 4.0, and realizes the multiple potential benefits and value addition in Lean manufacturing with AI, it will soon become a norm or even mandatory for assured productivity.

How Artificial Intelligence Is the Change Agent for Manufacturing Success

Data does not lie, and artificial intelligence creates transparency!

Change begins with an idea, and a change agent can make or break an idea or turn it towards becoming the next innovation.

That has always been true, but now more than ever before. The innovations that are changing the world are happening at lightning speed. Companies can launch an idea, iterate on it with customers, and scale it globally in the blink of an eye. We are talking about artificial intelligence, robotics, virtual reality, advanced materials, 3D printing, and more.

The Fourth Industrial Revolution is reshaping the world. New capabilities are getting rolled out daily. But are we thinking ahead of the curve or are we resisting the drivers of change? At the core of Industry 4.0 are transformational technologies such as Machine learning (ML) and artificial intelligence (AI), backed by Big Data — change agents that gave a solid foundation to the biggest revolution in innovation. Are you wondering why and how your business will get impacted? If you think this is another fad that people will eventually forget, here is our $0.02.

Let’s face it! Manufacturing success can be rare to come by. Even for the biggest and best manufacturers, it is a constant struggle to compete in a global economy. There are two perpetual goals of any manufacturing business — two qualitative and quantitative goals — increased output and improved efficiency, which fetch the ultimate goal of Golden ROI.

For starters, there is a lot that AI can do for optimized manufacturing. The best way to understand that is by breaking down each word:

• Output: AI can pinpoint where your company is experiencing loss in productivity and recommend ways to correct your processes. It could begin with detecting bottlenecks that cause WIP and also do as much as providing real-time guided production models that enable end-to-end synchronized production planning.

• Efficiency: Close at the heel of increased output comes efficiency through AI. The more efficient the workflow and production processes, the better revenue generated for the company. And that can also translate into increased investments in applications that can bring further growth. By utilizing this fantastic catalyst or change agent of business success called AI, companies can ensure optimized manufacturing.

And what is fueling those recommendations and insights from your AI applications? That which tells you where and how your processes are flawed? Big Data is the massive collection of information that gets analyzed by AI applications. It is from Big Data that companies can extract meaningful business insights. And that can help them optimize manufacturing, improve customer experience and satisfaction, and thus eventually gain an edge over market competition.

The demand for data-driven decision-making is growing as businesses enter the 4th industrial revolution (IR4.0). For some time, manufacturers have been looking for new ways to boost production while saving costs. Many turned to the internet of things (IoT), but data analytics with AI applications came as game-changers.

The power duo creates clarity out of complexity. Human perceptions and biases from experiences can obstruct the optimization of manufacturing. Whereas data does not lie, and data analytics give unbiased observations. It helps distill facts and creates transparency in operations. Artificial intelligence applications can provide integrated analytics and actionable insights in real-time. Manufacturers can achieve optimized quality production through timely informed decisions.

The report published by PwC based on their study conducted regarding Exploiting the AI Revolution says that AI could contribute up to $15.7 trillion to the global economy by 2030. Of this, $6.6 trillion is likely to come from increased productivity. Research has also suggested that 45% of total economic gains by 2030 will come from product enhancements, stimulating consumer demand. That is because AI will drive greater product variety, with increased personalization, while also reducing production costs considerably (PricewaterhouseCoopers, 2016).

So, understand, invest and embrace. Don’t just resist and reject. Informed and progressive decisions today will lead you to success in the future. And see if you can borrow some artificial intelligence to do that!

How IIOT Platforms are Getting Impacted by the Idea of Use Cases Driving Scalability and Accelerating ROI.

AI and use case-based applications are the future of IIoT, say experts and analystsWebinar Report

In the world of multi-dimensional data today, the traditional asset-centric and industry analytics IoT platforms can no longer provide competitive benefits or business impact. Thus, organizations are increasingly adopting Industry 4.0 and digitalizing their entire manufacturing value chain. Yet, while making this shift, many cannot understand the value and importance of the immediate impact that Digital Industrial Platforms can have on their manufacturing. 

In a virtual conference on ‘The Emergence of Use Case-Based Applications on Digital Industrial Platforms’ conducted on Tuesday 7th September 2021, industry experts and thought leaders joined us as our esteemed speakers. Dr. Marie-Isabelle Penet — Global Industrial Operation Excellence & Transformation Manager at Euro API (Sanofi) along with Dr. Zoltan Finta, Digitalization Global Leader at Euro API (Sanofi), Dr. Paul Miller — Principal Analyst at Forrester, and Mr. Jaspreet Bindra, Thought Leader in AI and Digital Transformation together with Neewee’s very own Co-Founder & CEO Mr. Harsimrat Bhasin discussed the future of Digital Industrial Platforms and their importance, and the generation of quicker ROI by the use case-based applications approach. 

Mr. Harsimrat Bhasin opened the forum to invite featured guest, Dr. Paul Miller. Based in the UK, his area of research coverage is the Smart manufacturing space. Miller astutely directed attention toward a 2015 McKinsey report that said 80 – 90% of industrial IOT pilots failed to scale. He also observed that the organizational issues and processes around it were problematic — not the technology. Thankfully, there was a paradigm shift. The formerly mum manufacturers began speaking up about their business problems in improving their processes for better yield rates, understanding how to deploy predictive maintenance, and focused on solving problems.  

Dr. Marie-Isabelle Penet and Dr. Zoltan Finta shared their real-world experience of overcoming their manufacturing problems and optimizing production with the help of Neewee. Penet spoke about how Euro API, being a part of a big company like Sanofi, made it imperative to manufacture consistent quality Active Pharmaceutical Ingredients (API) on a big scale for Europe. The challenge was to identify correct process parameters and control them while also improving productivity and quality profiles.  

When asked why they turned to Neewee in particular, Finta said, “We wanted to work with a company that has extensive experience in manufacturing digitalization. Because Neewee is flexible enough to not only understand chemistry but also understand our most specific problems; dedicated to working together on those problems relentlessly until we find a solution.” He also added, “With Neewee, it is not a connection as a customer and the supplier. No, this is a partnership.” 

Penet confirmed that Neewee’s structured approach afforded clarity on what to do, what results to expect; they saw measurable benefits within three months. 

“Major benefits of the collaboration with Neewee is that there are actionable insights for implementation, and they always conduct work with maximum transparency. We have had not only one collaboration, but we did it again,” she said with a broad smile. 

However, Finta said it was challenging to convince the management at their manufacturing plant. The experts with 20-30 years of industry experience came to the table believing that they knew everything about API manufacturing and that there was no scope or requirement for digital transformation. 

“Thanks to the collaboration culture with Neewee, there was a total openness in discussions of any idea or feedback. Their agile response to anything the manufacturing site needed. We only needed to wait for the site representative to recalculate and realize they had reached maximized results, quantified as maximum yield. The management then committed to digitalization.” 

Bhasin explained the Neewee perspective, “It’s having a shared goal, which is very important. What will be the ROI at the end of it? Because then you know what you are working toward. We are not experts in their chemical production processes. So, what we bring is the way of looking at data, which can drive that value. Collaboration helps to scale it up and make it a sustainable long-term success. When you quickly identify problems in production processes and show them hidden values, it’s the proverbial tasting blood. It becomes self-perpetuating at that point.”  

Miller made it a thought-provoking discussion by asking Mr. Jaspreet Bindra to comment on failing fast at scaling success.  

“Successful digital transformations are successful experiments. Successful for many reasons, but failing for only one reason — lack of the organizational culture mindset.” Said Bindra. “A company becomes digital when it starts thinking and behaving in a different way. Business models must change to focus not only on the technology but also on customer problems,” Bindra added. 

As the webinar drew to a close, Bhasin spoke about how Neewee has helped Sanofi with initial success and digital transformation at a few plants and what is being done to replicate it globally across the entire organization in the future. 

“One is to have a solution that can work seamlessly across different sites similarly. Second, giving the same level of confidence to the management that we can deploy solutions rapidly. And last, giving on-ground actual users actionable insights,” Bhasin replied perceptively, adding, “Paul, sometimes you have to start small to show the success. Confidence in newer ideas builds upon success, and then it grows in circles, getting bigger and bigger!” 

The webinar ended on a high note with Finta’s words, who spoke like a true visionary, “Machine learning and artificial intelligence is a part of our digital transformation. I think that the future is to scale up what we started together with Neewee. The key element is to get reliable master data for data analysis. And instead of just one or two projects, we need to think 20 or 25. When the different digital tools get connected, we could use the same collected data for different purposes. We must not only scale up the fund to expand the portfolio but also increase it, to finally embrace the digital industrial platform in its entirety!”