Where and how digital manufacturing is developing?

Digital manufacturing has fundamentally changed the direction of industrial production, but companies need to think about where this trend is going and how to adapt to these changes. Manufacturers are using technologies like automation, artificial intelligence, and the Internet of Things to help them stay competitive and future-proof their operations while also increasing productivity, quality, and agility. Some of the major developments in digital manufacturing include data-driven strategies, networked manufacturing for waste reduction, AI-driven continuous improvement, on-demand 3D printing, and advanced robotics for accuracy and productivity gains.

The intriguing thing is that, in spite of the drive for digital manufacturing, the majority of businesses have not yet fully implemented the concepts in their facilities. Indeed, according to a recent L2L poll, only 30% of manufacturers said their companies intended to invest more on digital transformation. It appears to me that technology is developing more quickly than most manufacturers are digitally maturing, along with consumer aspirations. They must, however, plan their operations around the future of industrial work in order to stay ahead of the competition, which goes beyond simply digitizing their plant.

Some of the key technologies involved in digitizing manufacturing processes include:

  • Internet of Things (IoT)
  • Connected worker platforms
  • AI and machine learning (ML)
  • 3D printing (Additive manufacturing)
  • Big data and analytics
  • Robotics and automation
  • Cloud Computing

Manufacturers adopt digital manufacturing technology for various purposes, including enhancing Overall equipment effectiveness (OEE) and gaining better insight into shop floor activities. This shift aims to boost employee retention and strengthen business resilience. A recent study by Gartner shows that 80% of CEOs are increasing their investments in digital technology to address ongoing economic challenges. Here are some of the most common goals of shifting from traditional to digital manufacturing:

  • Cost reduction: Streamlining processes, reducing waste, and automating repetitive tasks contribute to lower operational costs for manufacturers. For instance, IoT sensor-driven predictive maintenance can help reduce equipment failures and the costs that accompany them.
  • Agility and flexibility: A digital factory provides enhanced flexibility in the manufacturing process, enabling manufacturers to swiftly adjust to changes in product specifications or fluctuations in market demand. This adaptability increases competitiveness and minimizes lead times.
  • Data-driven decision-making: Manufacturers gather extensive data from various sources, including sensors, machinery, and their workforce. By analyzing this data in real time, they can make well-informed choices regarding production, supply chain management, and resource distribution.
  • Enhanced customer experience: Manufacturers focus on improving customer interactions through digital communication, personalization, and support channels. By leveraging customer data obtained through these digital platforms, they can refine their product development strategies.

Digital transformation enables manufacturers to achieve a broad spectrum of objectives. Additionally, digital manufacturing allows them to accomplish these goals more swiftly than traditional methods, helping them maintain a competitive edge and adapt to market changes. Digital manufacturing is progressing towards practical applications, although it will require time to fully materialize. Recent estimates indicate that only around 26% of companies have implemented some form of digital manufacturing — these are the "frontrunners." These frontrunners recognize the significant advantages that new technology brings to digital transformation in manufacturing. Their primary competitive edge lies in the fact that they were among the first to adopt these innovations.

The digital manufacturing revolution is anchored in five interconnected trends that are currently emerging: 

  • Data-driven. Airbus leverages digital innovations to create added value for both its customers and technicians. Their open-data platform, Skywise, provides tools for fleet analysis, efficiency tracking, and predictive maintenance. The platform’s analytics capabilities help the company reduce fuel consumption. To date, over 12 airlines and 2,000 aircraft have been linked to this digital system.
  • Connected. Networked manufacturing enables waste reduction, enhanced predictive maintenance, and greater flexibility. In this model, customer demand drives the supply chain, leading to production systems that accommodate smaller batches and customized product offerings. For instance, global fashion retailer Zara employs connected technologies to swiftly respond to customer preferences, decrease supply chain expenses, and allow staff to manage store inventory simply by using a small handheld device on clothing racks.
  • Artificial intelligence (AI) is transforming the landscape by understanding its intricacies and utilizing that knowledge for ongoing enhancements. In collaboration with Google, Andrew Ng, a former Baidu innovator, established Landing.ai, a platform aimed at integrating artificial intelligence into the manufacturing sector through computer vision technology. This platform can enhance an organization’s digital maturity, driving evolution in line with a digital transformation strategy.
  • On-demand components stem from the trend of 3D printing, also referred to as additive manufacturing. Boeing employs this method to produce non-flight critical parts for military aircraft. On-demand or direct digital manufacturing (DDM) allows for the seamless creation of components. This process takes designs from a computer and turns them into actual parts while opening up a plethora of new opportunities. Speed represents just one benefit; a significant advantage is that it eliminates the need for a complete manufacturing line and avoids the necessity for retooling for minor or new modifications.
  • Robotics plays a crucial role in automation, a core principle of digital transformation within Industry 4.0. This technology facilitates a degree of precision and productivity in processes that far surpasses human capabilities. Furthermore, robotics in manufacturing can incorporate voice and image recognition to replicate tasks that typically require human intervention. It’s manufacturing firms that will invest the most in robotics — because manufacturing businesses have the most to gain.

Without making technological investments, a revolution in digital manufacturing is unthinkable. Businesses must first purchase the equipment and software that will power this shift before developing a thorough plan for digital transformation. Making this shift is difficult for many manufacturers, though. 

**********************
*****************
******

 

Comments

Post a Comment

Popular posts from this blog

Generative AI & Meta-Leaders

In the wake of advances in generative AI and large language models (LLMs), there is excitement about what the technology means for businesses. But we should not forget that this advancement is also posing a catch-22 situation to the traditional leadership. The transformative potential and rapid acceleration of generative AI are creating an imperative for them to act quickly. They should rethink their skillsets and develop new skillsets like – ability to make better sense of data insights, ability to ask better questions, ability to learn from smart mistakes etc. It is true that ChatGPT has taken the world by storm. In just 5 days since its launch in November last year, it gained one million users, a feat that no other popular online services have managed to achieve. But it is not the only generative AI tool, others include Midjourney and Dall-E for images generation, GitHub Copilot for coding, and even conditional generative adversarial networks (cGAN) such as Pix2Pix, developed by ...
Read more

Good automation! Select right process for RPA

Someone said very rightly – “Automation is good, so long as you know exactly where to put the machine.” In all my previous blogs I wrote about BOT failure, ROI Modelling, Cost saving, RPA Governance, CoE, POC, POV etc. But then I realized that before taking a deep dive into any of these subjects, first we need to have a right RPA process identification & prioritization methodology in place. Everybody across the industry agrees that Robotic process automation (RPA) can make a big difference for organizations tormented by repetitive routine processes – the kind that suck up the productivity of people whose time would be better put toward more important work. But many are confused by what seems to be a deceivingly simple question — which are the right processes for RPA? The poor choice of process for initial pilot is the leading root cause for failure to meet customers’ expectations. Robotic Process Automation (RPA) doesn’t suit every process and in majority of cases we don’t have...
Read more

RPA Exception Handling – Be in control

Companies in every major industry are turning to semiautonomous computers (better known as BOTs) to automate large- and small-scale business processes. This technology replaces human intervention in back-office operations, improving operational efficiency, reducing costs and increasing margins. However, organizations cannot employ this technology effectively unless the BOTs are engineered properly. And one of the most important component of this BOT engineering is Exception handling or in simple words right categorization of the errors and then developing solutions around the same to deal with those errors to meet the expectations of the RPA owner. Occasionally, in the course of its work, an RPA BOT definitely encounter a situation it was not programmed to handle – and, in those cases, it will stall. Those cases can be for foreseeable reasons – security or access constraints – or it can be for unforeseeable reasons – like missing or incorrect data. Increasingly, RPA developers are ab...
Read more