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Industry 4.0: 7 Practical Case Studies of Digital Manufacturing

A Brief Overview of Industry 4.0

Industry 4.0 is indicating a shift in the status quo of traditional production. The three technical themes driving this transformation—connectivity, intelligence, and flexible automation—are collectively referred to as Industry 4.0, or the Fourth Industrial Revolution.

In order to create a cyber-physical environment, Industry 4.0 combines OT (Operational Technology) and IT (Information Technology).

The emergence of digital solutions and cutting-edge technology, which are frequently linked to Industry 4.0, have made this convergence possible. These consist of:

Internet of Things for Industry

Huge Data

Utilizing the cloud

Production Using Additives (AM)

Modern robotics

Virtual and augmented reality (AR/VR)

Through the integration of previously disjointed systems and processes through interconnected computer systems across the value and supply chain, these technologies are assisting in the digital transformation of manufacturing.

Embracing Industry 4.0, digital manufacturing, and the connectedness that comes with it offers businesses a wide range of advantages, including increased operational performance, agility, and flexibility.

Internet of Things for Industry

The Internet of Things is at the core of Industry 4.0. (IoT).

Simply put, the Internet of Things (IoT) is a network of physical objects that are digitally linked together to enable communication and data exchange through the Internet. Anything from cellphones and home appliances to cars and even structures might be considered smart gadgets.

A subset of the Internet of Things called industrial IoT integrates numerous sensors, RFID tags, software, and electronics with industrial machinery and systems to gather real-time data on their performance and health.

 

IIoT has several potential applications. Today, managing and tracking assets is one of the technology's most crucial functions.

IIoT can be used, for instance, to stop inventory from being overstocked or understocked.

Installing sensors and weights on the shelves and sending stock-related data to your warehouse management system is one approach to achieve this.

Warehouse managers can monitor inventory levels and have real-time access to and control over it by setting up a system like this.

Let's look at how BJC HealthCare reduces costs in its supply chain by utilizing an integrated inventory management solution.

Spotlight: BJC HealthCare uses IoT for supply chain and inventory management

A company that offers medical services is BJC HealthCare. It manages 15 hospitals in Illinois and Missouri.

Radio frequency identification (RFID) technology is used by the business to track and handle thousands of medical goods. RFID technology reads and stores data on tags that are affixed to objects, such as medical supplies, using radio waves.

Inventory tracking used to be a labor-intensive manual process. However, due to the large number of various items hospitals purchase from suppliers and the large number of items they keep on hand for particular operations, physically maintaining inventory can be challenging.

When stock is lost, it may be necessary to closely monitor product expiration dates and spend a lot of time conducting inventory inspections.

These factors led BJC to choose to use RFID tagging technology in 2015.

BJC has been able to cut the amount of stock held on-site at each plant by 23% since introducing the system. Once RFID tagging is fully implemented this year, the company anticipates continuous savings of about $5 million each year.

This illustration shows how IIoT may greatly enhance operations, boost efficiency, cut costs, and offer useful real-time visibility throughout the supply chain.

Data Analytics and Big Data

 

 

The term "big data" describes the enormous and intricate data sets produced by IoT devices. These data arrive in a variety of forms and protocols from a wide range of cloud and business applications, websites, computers, sensors, cameras, and more.

In the manufacturing sector, there are many various types of data to take into account, including databases from ERP, CRM, and MES systems and data from production equipment fitted with sensors.

But how can manufacturers transform the data they gather into actionable business insights and tangible benefits?

The analysis of data.

Data analytics are crucial when it comes to transforming data into knowledge that might yield useful insights.

Processes involving data analytics can be aided by machine learning models and data visualization. Data visualization technologies make it possible for manufacturers to more quickly understand the story the data tells, while machine learning approaches, in general, utilize strong computer algorithms to handle enormous data sets.

Ultimately, businesses are now able to discover new approaches to enhance the processes that have the biggest impact on production by taking previously isolated data sets and collecting and analyzing them.

Big Data Decision-Making at the Bosch Automotive Factory in China in the Spotlight

In order to accelerate the digital transformation of its Bosch Automotive Diesel System manufacturing in Wuxi, China, Bosch is combining IIoT and big data.

At the heart of the factory, the corporation connects its equipment to monitor the entire production process. This is accomplished by integrating sensors into the machinery in the plant, which are then utilized to gather information about the state of the machinery and its cycle time.

Advanced data analytics systems analyze the data after it has been gathered in real time and alert workers to potential production bottlenecks.

This technique aids in predicting when equipment will malfunction so that the factory can schedule maintenance work well in advance of any breakdowns.

Because of this, the manufacturer is able to keep its equipment working for extended periods of time.

 

According to the business, using data analysis in this way has helped raise output by more than 10% in some sectors while enhancing delivery and customer satisfaction.

In the end, having more knowledge about the plant's operations helps the entire organizationmake decisions more quickly and effectively, reducing equipment downtime and streamlining production procedures.

Utilizing the cloud

For a very long time, manufacturers have been gathering and storing data to enhance their operations.

For a very long time, manufacturers have been gathering and storing data to enhance their operations.

However, with the development of IoT and Industry 4.0, it is now true that data is being produced at an uncontrollable rate and in enormous quantities, making manual handling of it impossible. A system that can store and manage this data more effectively is therefore required.

Cloud computing can help with this.

Cloud computing offers a platform for users to store and process massive volumes of data on remote computers. Organizations can use computer resources without having to build an on-site computing infrastructure thanks to it.

Information that is stored in the "cloud," "cloud," and accessed remotely via the Internet is referred to as "cloud computing." While not a solution in and of itself, cloud computing makes it possible to deploy other solutions that previously required significant computational capacity.

Businesses may gather and utilise business insight through the use of big data analytics thanks to the capabilities of cloud computing to provide scalable computer resources and storage space. They may consolidate and streamline their manufacturing and business activities thanks to this. Businesses may gather and utilise business insight through the use of big data analytics thanks to the capabilities of cloud computing to provide scalable computer resources and storage space. They may consolidate and streamline their manufacturing and business activities thanks to this.

Organization

IDC forecasts that in 2021, manufacturers will spend $9.2 billion on cloud computing platforms globally. A fundamental driver driving its acceptance is the benefit of becentralizecentralizeo centralise removing silos eliminating silos so that information may be shared throughout a whole business.

 

According to one IDC assessment, qualityquality controlcontrol, computer-aidedcomputer-aided engineering,engineering, and manufacturingmanufacturing executionexecution systemssystems (MES) are the three most extensively utilized systems in the cloud.

Clearly, cloud computing is revolutionizing practically every area of manufacturing, from workflow management to production operations and even product validation.

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