Hi I work for a manufacturing company that is sort of behind on technology. My role is an analyst with a focus on process Improvement. My goal is to bring machine learning to the company and apply it. I have a b.s in mathematics, but I just started learning machine learning on my own. I just finished a book called Pandas in 7 days, now I'm reading machine learning for everyone, and Josh Starmers new machine learning book.

In 2022 AI in Manufacturing is valued at USD 2.3 billion and is projected to reach 16.7 billion by 2027 according to a recent report. The result of adopting AI in any shape or form – from automation and predictive analytics, to natural language processing (NLP) and computer vision, can be seen in early adopters such as IBM, Intel, GE, Siemens, and their success and business growth. In this article, we'll take a look at just some of the ways manufacturing companies can benefit from implementing AI in their processes. Furthermore, we'll share the diverse applications of AI that will help you save costs and improve processes regardless of the product specifics. As Harald von Heynitz, Head of Industrial Manufacturing, KPMG has said "Taking advantage of advances in robotics, 3D printing, and AI is critical to driving greater efficiency, lowering costs, and improving safety for many sectors and particularly niche suppliers". The benefits AI brings to Manufacturing are twofold.

The amount of data to be stored and processed is increasing day by day. Therefore, today's manufacturing companies need to find new solutions and use cases for this data. Of course, data benefits manufacturing companies as it allows to automate large-scale processes and speed up execution time. Data science is said to have dramatically changed the manufacturing industry. Let's consider a few data science use cases that have become common in manufacturing and benefit manufacturers.

Artificial intelligence is anywhere, and we utilize it in our daily lives without even recognizing it. Artificial intelligence has produced a great deal of progress in recent years. It may affect many distinct businesses, and it is principally because of the improved algorithms, processing, and the quantity of information it holds. Machine learning provides the information to be examined, followed by crucial insights, plus it has a massive influence on the manufacturing industry. Cobots, known as collaborative robots, are all made to operate with people safely.

The topic of retrofitting, i.e., the modernization of machines and systems into the digital age, is also an important trend in terms of sustainability, energy saving and resource optimization that we are also serving. Our solutions for automation and quality assurance are used every day in numerous industries such as the automotive industry, the food industry and for mechanical engineering. From concept design to the integration of the finished system, and of course the subsequent support, we do everything in-house. Our vision is to continue creating innovative turnkey solutions, produce new products that are missing on the market and ensuring the future of quality assurance in the machine vision industry. Roman: "Due to great work experiences with American clients, we decided to enter the US market. Just like in Germany, we want to offer the US market our turn-key inspection solutions and services with the goal to guarantee the highest quality and offer our clients a high ROI with our full-spectrum machine vision systems."

Unpredictable spikes and drops in demand combined with chronic supply chain and labor shortages are accelerating the pace of digital transformation in manufacturing, starting with worker safety. Forty-eight percent of manufacturers say their progress on digital transformation initiatives has accelerated so much that it's years ahead of what was originally anticipated, according to a KPMG study. Keeping workers safe and connected is the primary goal of most digital transformation and hiring plans, with on-site distancing & workplace safety listed as the two highest priorities. The company's SENTRI360 platform proves effective in preventing workplace injuries and operational downtimes at several steel-heavy manufacturing companies, including Zekelman Industries and SeAH Besteel. From redesigning shop floors, to meeting social distancing guidelines, and doubling their investment in training and development, worker safety now dominates manufacturing -- even more so due to the pandemic.

Unpredictable spikes and drops in demand combined with chronic supply chain and labor shortages are accelerating the pace of digital transformation in manufacturing, starting with worker safety. Forty-eight percent of manufacturers say their progress on digital transformation initiatives has accelerated so much that it's years ahead of what was originally anticipated, according to a KPMG study. Keeping workers safe and connected is the primary goal of most digital transformation and hiring plans, with on-site distancing & workplace safety listed as the two highest priorities. The company's SENTRI360 platform proves effective in preventing workplace injuries and operational downtimes at several steel-heavy manufacturing companies, including Zekelman Industries and SeAH Besteel. From redesigning shop floors, to meeting social distancing guidelines, and doubling their investment in training and development, worker safety now dominates manufacturing -- even more so due to the pandemic.

Let's start with the basics. Digital transformation solutions not only bring automation in various processes but also provide actionable insights for making informed decisions. Whatever digital transformation in manufacturing offers, one thing is for sure, it can change the shape of the manufacturing sector. In a PwC survey, out of 2000 manufacturing enterprises, a whopping 86% expect to gain from reduced costs and increased revenue through digitization in the next five years. What's more, digital transformation in manufacturing enables the industries to leverage the benefits of Industry 4.0 and achieve new levels over the period.

Beyond hypes and fads, AI works because it amasses significant benefits for the manufacturing sector, such as enabling smart production, developing predictive and preventative maintenance, offering supply chain optimisation, improved safety, product development, and optimisation, facilitating AR/VR (Augmented and Virtual Reality), cost reduction, quality assurance and enabling green operations (energy management), to name a few. Manufacturing companies are adopting AI and ML with such speed because by using these cognitive computing technologies, organisations can optimise their analytics capabilities, make better forecasts and decrease inventory costs. We see that scaling AI implementations beyond a proof-of-concept (POC) level remains one of the biggest challenges in manufacturing, as well as other industries including but not limited to logistics, healthcare, insurance, finance and audit. For instance, even when people are aware that the inventory recommendations for raw materials or deliverables are accurate, they feel more comfortable holding a little extra stock or to be a little protective in the supply chain. Digital twins work by essentially evolving profiles of past and current behaviours of physical objects or processes that can be effectively analysed to optimise business performance.

The pandemic has accelerated the adoption of technology for many companies. Governments are developing strategies to encourage further adoption. However, many businesses are still wary of AI and require additional reassurance to go ahead, particularly in industries where implementation is slow. AI insurance is the solution to speed up adoption, says Saar Yoskovitz, co-founder & CEO of Augury. As the capabilities of AI solutions improve and development and implementation become easier, businesses are shifting their views and increasing the use of the technology.