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Beyond digitalization: Industry & Manufacturing 4.0

Illustration that represents Industry 4.0 and Manufacturing 4.0 | Scilife

Industry trends

In Industry 4.0, manufacturing environments undergo transformations driven by global changes and disruptive technologies like Artificial Intelligence, Big Data, Deep Learning, and the Internet of Things. Coined in 2011, at the Hannover Messe, Germany’s most important industrial fair, Industry 4.0 integrates information technologies, creating smart systems fueled by data and machine learning for more flexible and efficient working environments, optimizing processes in real-time.


As opposed to the fourth industrial revolution, Quality 4.0 focuses on maximizing quality culture, collaboration, competency and leadership, within a digital environment.



In Quality 4.0, quality professionals improve quality management by using the digital tools they have available today and understanding how to apply those tools effectively. In the face of digital disruption, quality professionals are becoming navigators rather than enforcers. They must be able to anticipate the digital disruption, understand the implications, and provide guidance and direction to their organizations in order to ensure that they can adapt and thrive.

Infographic that represents the evolution of Industry 4.0 | Scilife
  •  Industry 4.0 and Quality 4.0 empower drug manufacturers with real-time analytics, boosting efficiency and precision in every batch.

  •  Industry 4.0 and Quality 4.0 empower drug manufacturers with real-time analytics, boosting efficiency and precision in every batch.

  •  Industry 4.0 and Quality 4.0 empower drug manufacturers with real-time analytics, boosting efficiency and precision in every batch.

  •  Industry 4.0 and Quality 4.0 empower drug manufacturers with real-time analytics, boosting efficiency and precision in every batch.

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Key Takeaways

01
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By integrating Industry 4.0 and Quality 4.0, manufacturing environments can become more flexible and efficient with analytics-driven quality management systems that can help companies make informed decisions based on real-time metrics.
02
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With advancements in technology, smoother processes, cost reduction, and accelerated innovation are possible. In industries where companies are not yet digitally mature, reskilling and upskilling the workforce are crucial.
03
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As digital technologies expand, it is imperative that data integrity, security updates, employee training for cybersecurity best practices, and contingency plans be established to handle security breaches, technical problems, or cyber attacks quickly.

Opportunities and Threats

Opportunities

The integration of Manufacturing 4.0 and Quality 4.0 presents various opportunities:

Illustration that represents the opportunities of Industry 4.0 and Manufacturing 4.0 | Scilife

Analytics-driven systems

The current quality management systems are analytics-driven. They display metrics, KPIs, and trends on dashboards. Forecasts can be provided to facilitate decision-making. This reduces downtime and increases productivity.

Proactive decision-making

As technology advances, companies will be able to monitor their operations in real-time, identify potential issues before they occur, and make decisions based on more accurate data.

Adaptive management

It is likely that in the future, eQMS will guide us towards better management, and that it will even do so autonomously by learning how to anticipate potential issues and take the best decisions for different situations as they arise.

Connected work environments

Industry 4.0 and Quality 4.0 will probably become obsolete in the future as work environments become increasingly connected, intelligent systems become widespread, and processes become automated.

Data-powered transformation

Powered by data and predictive analytics, eQMS will make more accurate predictions, respond to changing conditions quicker, make smarter decisions, implement smoother processes, reduce costs, and accelerate innovation.

Threats

On the other hand, the integration of Manufacturing 4.0 and Quality 4.0 presents various challenges:

Illustration that represents the threats of Industry 4.0 and Manufacturing 4.0 | Scilife

Navigating initial costs

Due to upfront costs, small and medium-sized enterprises may be unable to finance the transition to Manufacturing 4.0 and Quality 4.0 technologies, resulting in low adoption rates and a deficit in
digital skills.

Digital maturity gap

Only 20 percent of biopharma companies are digitally maturing (Standing M. & Reh.G, 2018). There is a need to reskill and upskill the workforce to operate and maintain advanced technologies as a result of automation.

Analysis paralysis

Analysis paralysis, where extensive upfront analysis precedes digital transformation, can lead to delays and resource consumption. This risk arises from investing significant time before initiating changes, potentially stalling momentum and delaying implementation.

Safeguarding data integrity

Interconnection relies on communication among machines, sensors, and humans. Protecting sensitive information and ensuring data integrity have become increasingly important with the growth of digital technologies.

Unauthorized access risks

Unauthorized access to data is a major concern. Communications must be protected and are vital to the successful implementation of Industry 4.0. (Toth, P., 2022).

Building a resilient future

Maintaining robust contingency plans, investing in ongoing employee training on cybersecurity best practices and regularly updating cybersecurity measures will be crucial to prevent technical issues, cyber attacks, or system failures.

Solution

One top application of Industry 4.0 and Quality 4.0 in which manufacturers are finding value is in advanced predictive maintenance.

Traditionally, maintenance methods rely heavily on corrective maintenance, which is reactive in nature, in which equipment is used until it fails, and then repaired or restored to its original condition.

Failures are unpredictable in terms of when they occur and how long they will last, so a company cannot prepare for such events, leading to potentially costly consequences.

In contrast, predictive maintenance strategies based on machine learning algorithms are increasingly being utilized to predict equipment failures and schedule maintenance ahead
of time.

By collecting data over time, patterns can be identified to predict and prevent failures, ultimately increasing reliability, reducing maintenance, and increasing equipment availability.

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Illustration that represents the Scilife View, opinions and insights from Scilife Experts around Industry 4.0 and Manufacturing 4.0 | Scilife

Scilife view

Image that represents the conclusions of Industry 4.0 and Manufacturing 4.0 Analysis | Scilife

Life sciences is experiencing a transformational era. Industry 4.0 enables efficient, agile manufacturing, providing the opportunity to reduce costs and accelerate time-to-market. Quality 4.0 uses advanced technology to foster continuous improvement through proactive quality monitoring. As a result, the industry gains a competitive edge in delivering superior products efficiently through the synergy of these advancements.

Illustration that indicates how to download the Report about the Quality trends in 2024 | Scilife

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