A short guide to productivity in manufacturing

Over the past month, we have been researching how to improve productivity in manufacturing settings. Below is a compilation of the most interesting articles and their key takeaways.

Content Overview

  1. Top 10 trends in manufacturing
  2. Industry 4.0 – Explained
  3. How to measure productivity in manufacturing
  4. Top 3 reasons why tracking workforce productivity in manufacturing is key
  5. Monitoring industrial processes with IoT sensors and positioning technology

1. Top 10 trends in manufacturing

Source: The 10 biggest future trends in manufacturing

Manufacturing is being completely reimagined. This Forbes article gives a great overview over the top 10 technological trends transforming manufacturing right now.

1. Industrial Internet of Things (IIoT)
Interconnected devices are used within the industrial setting to collect data and enhance manufacturing processes.

2. 5G & edge computing
5G is enabling manufacturers to easily and reliably connect IIoT technologies and subsequently leverage the data collection and processing within the smart devices and sensors, without compromising on security and speed.

3. Predictive maintenance
Sensor data and AI are being leveraged to detect failure patterns in machines and components before they occur.

4. Digital twins
Digital simulations of the physical world are used to create replicate and optimize manufacturing processes and objects. We have extensively written about Digital Twins here and here.

5. Extended reality and the metaverse
Using augmented and virtual reality will increasingly allow manufacturers to enhance product design, production planning and develop immersive training.

6. Automation and dark factories
Increasing automation is slowly allowing for dark factories which are fully automated manufacturing sites that do not require any human intervention.

7. Robots and cobots
Increasingly we are seeing the symbiosis between humans and machines where we can leverage robots as “cobots”, machine-based coworkers, that can help with tasks such as the heavy lifting of equipment without compromising safety.

8. 3D printing
3D printing is becoming more cost-effective, scalable and efficient. This enables manufacturers to cut prototyping time and accelerate the pace of innovation.

9. Web3 and blockchain technology
Distributed computing technologies like blockchains and NFTs allow manufacturers not only to improve the monitoring of their supply chains but also to automate transactions across the value chain.

10. Smarter, more sustainable products
Today customers expect “smartness” in almost every device. The demand enables manufacturers to track and improve the sustainability of their products even beyond the time they leave the assembly line or retail shelf.


2. Industry 4.0 – Explained

Source: The fundamentals and impact of Industry 4.0

Industry 4.0 is a buzzword that can be hard to define. This article does a great job of explaining its fundamentals, opportunities, and critical features. Here are the key takeaways.

Fundamentals

Industry 4.0 is all about creating smart factories through the digitalization of manufacturing processes in which minimal human intervention is required. This is achieved by connecting computers and machines to communicate with each other via software platforms, internet of things (IoT), and internet of services (IoS).

Opportunities

Intelligent factories that leverage Industry 4.0 technologies can increase revenues, decrease operational costs and improve asset efficiencies. More specifically, customers of Industry 4.0 applications expect:
·     Reduced downtime by 35%-40%
·     Improved production by 15%-20
·     Improved product quality by 35%-40%
·     Improved overall productivity by 65%-70%
·     Improved asset utilization by 35%-40%

Key Features

One of the reasons Industry 4.0 is hard to define is due to its enormous scope. Below is a list of use cases that can give you a rough overview of what comprises Industry 4.0, as well as serve as a starting point for further research:
·     Digital Twin
·     Preventive and predictive maintenance
·     Machine and part history
·     Operator mapping
·     Machine health and tool life
·     Real-time efficiency and OEE analysis
·     Downtime analysis
·     Quality control
·     Production planning
·     Condition-based monitoring
·     Report automation
·     Robotic process automation


3. How to measure productivity in manufacturing

For manufacturers embarking on the Industry 4.0 journey, new ways of tracking the productivity of their labor force are arising. Before we talk about relevant tools such as sensor and IoT technologies, it is important to understand how to measure productivity. Here are the 2 most common ways for measuring productivity within manufacturing:
 
1. Efficiency metrics: the amount of time it takes to complete a specific task or workflow, essentially productivity linked to time
 
2. Output metrics: the higher-level value produced in terms of revenue or profit margins, essentially productivity linked to corporate goals and finance
 
Efficiency metrics are easily tracked since they can be isolated to a single task or process (e.g., think of items assembled, units picked, etc.). With modern sensor technologies, manufacturing processes can be broken down into their individual tasks and efficiency metrics for each can be measured and compared across locations and time.
 
In contrast, output metrics are harder to measure since they require revenues that are generated by the overall manufacturing process to be attributed to the individual processes. However, when done right, output metrics can be more impactful since they are tied closely to the corporate goals and provide the most important understanding of productivity, the financial impact.


4. Top 3 reasons why tracking workforce productivity in manufacturing is key

Source: Tracking productivity in Industry 4.0

Every manager knows that improving productivity is important for the business, but is it also for employees? And does it justify measuring it? An article in Construction argues that it is and explains how it will impact your workforce. Here are the key 3 takeaways on why you should track productivity amongst your (manufacturing) labor force:

1. Higher employee engagement

When you provide your employees transparently with their unbiased productivity metrics and put in the right incentives, they will start collaborating and improving performance bottom-up.

2. Understanding of dependencies

Capturing different productivity metrics and feeding them into one single platform you will start to see how changes in productivity upstream can affect productivity downstream, leading you to potentially deploy more human resources upstream for certain workflows.

3. Identifying automation opportunities

Jobs that are comprised of non-creative repetitive tasks are not the most fulfilling ones for humans. For some, we do not have yet the right machines to replace human labor. However, for the ones we do, tracking your employee’s productivity will allow you to directly compare it with the next-best machine-based solution. This will enable you to identify automation opportunities and create win-win for both, the employees and the business.


5. Monitoring industrial processes with IoT sensors and positioning technology

Source: Sensor data beats employee labor every time

This article goes into more detail about how IoT solutions can help your industrial processes.

In essence, to maximize your manufacturing productivity, give creativity-related tasks to humans and repetitive tasks to machines. Monitoring and reporting on industrial processes falls into the latter camp and can be done with sensors and positioning solutions. Easier said than done. This article goes into more detail on which use cases you can automate using sensor data such as Forkbeard’s indoor positioning system.


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