Guide Direct Engineering: Toward Intelligent Manufacturing

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Direct Engineering: Toward Intelligent Manufacturing.
Table of contents

This increased specialization, in particular, has become a driving force of global value chains. As manufacturing activity and the focus on new products evolve, there is increased potential for manufacturing activity to move back toward high-wage areas. This may flip the story of the previous several decades, during which knowledge centers grew in high-wage areas and component production occurred elsewhere.

As technology progresses, however, it is likely that this dynamic will have to change as well, a fact that has impacted the recent trade talks between the United States and China. As tariffs have been proposed and trade arguments have risen in prominence, questions of intellectual property IP and positions in the supply chain have become essential to trade discussions.

China has agreed to gradually eliminate its restriction on foreign ownership, reversing a long period of limitations intended on elevating domestic Chinese IP. This deregulation appears to follow in line with intelligent manufacturing trends. As manufacturing activities require less and less physical labor, it becomes increasingly important for states to entice leading companies to establish domestic locations.

Average wages in the manufacturing sector have been steadily increasing. According to data from the Bureau of Labor Statistics, when indexed to , output per hour in the manufacturing sector increased from As technology has progressed, data aggregation and sharing at each stage of the manufacturing process has resulted both in greater efficiency but also in a blurring of industry distinctions. As a result, IT departments are expanding, and companies are using acquisitions to generate new value propositions with technology. Networked machines, for example, are beginning to fully automate and optimize production.

A production machine can now detect a potentially dangerous malfunction, shut down other equipment that could be damaged and direct maintenance staff to the problem. This newest stage of technological change has caused a divergence from recent long-term trends. As production became more efficient through robotics and process tracking, US manufacturing labor became rapidly more productive.

Additionally, this has not simply been restricted to high-technology industries. More recently, sector-wide manufacturing trends have shifted slightly with the current technological revolution. Do you need to start somewhere? Yes, and you can. Is it, even if fear is a bad advisor, time to sprint to value in Industry 4. Looking at what the best in class are doing we would say yes.

Moreover, there are some predictions you might want to look at, such as this first one from an IDC article with 10 predictions for the manufacturing industry , as summarized end By , only 30 percent of manufacturers investing in digital transformation will be able to maximize the outcome; the rest are held back by outdated business models and technology. Several of them are also explored more in depth in other articles on this site. The essential goal of Industry 4.

Most of the benefits of Industry 4. As mentioned in the section on the state of Industry 4.

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In other words: saving costs, increasing profitability, reducing waste, automating to prevent errors and delays, speeding up production to work more in real-time and in function of the overall value chain, where speed is crucial for everyone, digitizing paper-based flows, being able to intervene faster in case of production issues and so forth. On top of the research from BCG we mentioned earlier, the signs that investments are done in these areas first are clear.

While we just mentioned speed in a context of optimization, automation and enhanced productivity, it is a benefit in many other ways as well. A lot of the productivity improvement benefits are rather about the internal goals of costs and process optimization. Yet, at the same time several also fit in a perspective of enhanced customer-centricity. If you look at the entire value chain and ecosystem within which manufacturing operations reside there are many stakeholders involved. These are all customers. And customers also want enhanced productivity, regardless of where they sit in the supply chain.

If the final customer wants good products fast and has increased expectations regarding customer experience, quality, service and products that are delivered on the exact time they want, this impacts the whole supply chain, all the way up to manufacturing and beyond. Moreover, customers simply expect it.

The more data you gather early on and the more timely this data gets where it matters when it matters, the more value down the supply chain.

In fact, this is the essence of one of the three dimensions of RAMI 4. When an industrial asset gets broken it needs to be fixed.

Direct engineering toward intelligent manufacturing

That costs time, money and very often a lot of moving around by support people and engineers. Production is affected, costing loads of money and unhappy customers, and sometimes production can be fully disrupted. If industrial assets are connected and can be monitored health status monitoring, for instance through the Internet of Things and issues are tackled before they even happen the benefits are huge.

Alerts can be set up, assets can be proactively maintained, real-time monitoring and diagnosis becomes possible, engineers can fix issues, if they do occur from a distance, the list goes on. No wonder that asset management and maintenance are the second largest area of IoT investments in manufacturing.

We mentioned that customers want speed. If you have everything in your production system and its broader environment hooked up with sensors, software, IoT technologies, systems of insight AND the customer, you can also enhance quality of your products. Automation definitely plays a big role here and so do the typical components of cyber-physical systems more below and the Internet of Things whereby quality aspects can be monitored in real-time and robots reduce errors.

On the flip side and one of the risks and challenges to tackle, as mentioned earlier: the more you automate, the less work for people, in theory. And the same goes for other mentioned benefits such as maintenance the less you need engineers for support, the less support engineers you need.

Direct Engineering: Toward Intelligent Manufacturing

In the meantime do know that robots are not going to take all human jobs over soon. Ample companies have increased the usage of robots and at the same time hired more. The reason we mention it in the context of quality is that this is certainly one area where you see cobots popping up cobots is a fancy term for advanced collaborative robots or put more simply: robots that fit a collaboration between man and machine. Talking about people, the human and social dimension is ubiquitous in Industry 4. Moreover, if we look at the possibilities and benefits, that human, social and even environmental aspect is key in the goals of Industry 4.

Improving working conditions based on real-time temperature, humidity and other data in the plant or warehouse, quick detection and enhanced protection in case of incidents, detection of presence of gasses, radiation and so forth, better communication and collaboration possibilities, a focus on ergonomics, clean air and clean factory initiatives certainly in Industry 4. We all know it: consumer behavior and preferences have changed.

Digital tools have changed the ways we work, shop and live. On top of that consumers also like a degree of personalization, depending on the context. Take sports shoes, for instance. Once a few colors of the same shoe were enough, know we want the ability to customize them in whatever way. On top of that another phenomenon is taking place and it does disrupt traditional supply chains. Consumers increasingly get and want possibilities to have a direct interaction with a brand and its manufacturing capability. Digital platforms to customize products as mentioned, shortened routes between production and delivery, possibilities to co-create and so on.

In many manufacturing environments these things already happen. If you want to offer these services at scale and even turn them into a competitive advantage, automation and several technologies and processes in industry 4. A real-life example without disclosing the details: a large bank wanting specific office equipment to use across all its branches customer-facing context with its own look, feel and features as part of a rebranding.

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There are plenty more examples. Now that we speak about competitive benefits and customization we also need to tackle agility, scalability and flexibility. The same scalability and agility which we expect from supporting IT services and technologies, such as the cloud, are expected in manufacturing. This is partially related with the previous topic of customization but mainly is about leveraging technologies, Big Data, AI, robots and cyber-physical systems to predict and meet seasonal demand, fluctuations in production, the possibility to downscale or upscale; in other words: all the adjustments that are sometimes more or less predictable, can be made more predictable or are not predictable but can be handled thanks to increased visibility, flexibility and a possibility to leverage assets in function of optimal production requirements from a perspective of time and scale.

Digital transformation, as you can read in our digital transformation strategy overview, is a matter of many levels, steps and capabilities. You can transform processes, specific functions, customer service, experiences and skillsets but in the end true value is generated by tapping into new, often information-intensive, revenue sources and ecosystems, enabling innovative capabilities, for instance in deploying an as-a-service-capacity for customers, advanced maintenance services and so on. In the end, Industry 4.

You can read more about it in our article on the digital transformation of manufacturing. Does this mean it is just a vague idea? No, on the contrary. What we do see indeed though is that most organizations are still in the early stages of preparations for Industry 4. Yet, the vision of Industry 4.

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Digital transformation, although being academically looked upon and despite the existence of numerous digital transformation frameworks and roadmap strategies, which are developed by numerous people, has no universal definition nor clear industry-wide approach. The same goes for the implementation of the Industrial Internet of Things. Just like digital transformation and the Industrial Internet of Things, adoption of Industrie 4.

However, Industry 4. In essence this means that in Industry 4. That is pretty unique.

So, just like digital transformation, Industry 4. Yet, as opposed to digital transformation this vision and reality is far more studied, documented and standardized despite the mentioned need to work in the context of the individual business as well. In the Industry 4. One such maturity approach looks at the information and actual operations and manufacturing systems perspective with autonomous machines and systems as true Industry 4.

In this gradual approach, whereby each stage builds upon the next one and adds more value, we move from data to information to knowledge to wisdom and action from a data perspective.