Energy Optimization of a CNC Machine
Introduction
Machine tools are the backbone of industry. As targets of production have been changing over time the expectation from machine tools has been also chaining. The first expectation from machine tools as it was invented in the late 1700s, is to be reliable for production. In the 1900s by emerging automobile factories the modern society needed to produce as many as possible 24/7. At this time machine tools have to be robust for three shifts running. During the space era after World War II, complex systems were developed. Humans go to the moon. In the 1990s computers found their space in production and lean production requires the machine tools to be time efficient. In the 2020s global warming brings the idea of sustainability to production.
This concerns pushing machine tools toward more energy efficient in producing a part and consequently to reduce energy in industry. Industry is responsible for 23% of total greenhouse gas emission and Machinery is responsible for 2% of that [1]. The opportunity to reduce the carbon footprint of a machine tool is very high. Machine tools are sustainable and energy efficient in all aspects from the final machined product up to recycling the old machine tool.
Design: components and the structure of machine tools to be energy efficient
User behaviour: Programming
Maintenance: cleaning and maintenance of components
Lubricant biobased: Instead of petroleum-based lubricant
Long life: Using machine tools for a long time with aim of the keeping them in the economy for as long as possible
Refurbish: Modular design provides the opportunity to replace and upgrade components in old machine tools.
Recycle: Machine tools can be recycled at the end of his life [2].
Industry 4.0
Industry 4.0 has been also developing in this era which is a catalyst to accelerate the sustainability in production, if it is applied in the right direction. Industry 4.0 aims to install IoT devices and collect data from manufacturing then using this data to improve production. AI-driven software will intervene between humans and machines to better adjust the machining process.
Two requirements are needed to have machine tools ready for industry 4.0.
1) Install sensors to acquire data from machines (IoT). There are suppliers of motors and controllers which already install proper sensors in their product to measure the energy consumption of their devices.
2) Cloud platforms to store data. There are well known companies who provide these services in high quality, however it is possible for any individual company to install their own database to store their data.
The technology for these two requirements is fully developed and it is available in the market at an affordable price.
Next step is optimization of the machine tools to be more energy efficient. The idea in 4i4 ApS is “keep it simple”. Although there is enough data to implement big data and do some huge cloud computational analysis, we intend to focus on small but more promising energy reduction. The first step is to optimise the structure, spindle and motor speed, tool and other effective hardware and software to reduce the energy.
After that optimization of the parameters of machining based on minimum energy consumption will be implemented. The first parameter to monitor is the temperature. If the temperature keeps on minimum then the 1) lubricant will be reduced. Moreover 2) the pumps for cooling fluid and filter are adjusted to work less since. However 1) for removing chips it is needed to use an air compressor which again consumes power. 2) The time of machining increases which increases the power consumption. So it is an optimization problem which is better to solve with AI.
CNC test stand
It is important to train the AI algorithm with clean and perfect data. For this reason, 4i4 is set up as a small CNC machine with a high speed IBAG spindle and a 5 axis Fanuc controller. The controller is equipped with an energy saving algorithm which provides a feature to compare traditional and energy saving machining programs.
Design criteria for the machine tool
- Workpiece size: 200 x 200 x 200 mm
- Workpiece material: Aluminium 6000 series
- Workpiece mass 35 kg
- Accuracy ±20µm
- Repeatability ±5µm
- Design life 30000 Hrs
Initial assumption
- Cutting Force 500 N
- Max feed rate 500 mm/s
Other information
Use MITCalc – Power and Ball screws
Gear ratio 1/1
Motors Fanuc Beta iS 0.5/6000, one motor with break for z axis
Motor and controller Fanuc. It is energy saving with energy monitoring
Fanuc energy saver CNC which provides inputs for motor power.
Ball screw diameter 15 mm
Ball screw lead 5 mmm
Ball screw stroke 300 mm
Useful link
Linear guide video series: Misumi linear motion series
Ball screw: Misumi ball screw
A problem with cheap ball screw and how to adjust it: Fixing Wobble Z
How to install linear product: NSK
As the machine tool is ready to use, it is validated by ISO 14955 & ISO 230.
Experience in energy flow visualization
The last experience in breakdown of a 5 axis CNC machine and visualisation of energy flow in the machine tool helps 4i4 to implement this idea with some modification to this project.
This idea is developed as a project is performed in a collaboration between DTU and ETH Zurich. Based on EU legislation companies should reduce their carbon footprint and the machine tools sector is responsible to move towards energy efficient machine tools. In this project energy flow in a 5 axis machine tool is measured and visualised in order to find which component consumes more power. The experience gained from this research is
- Installing temperature, fluid, current and power sensors
- Data acquisition by LabVIEW
- Energy flow visualisation by Sankey diagram
- Proper use of documentation of machines to reduce measurement
- Verify experiment by the rule of energy conversion
The result shows the cooling system consumes the main part of energy, which can be a target to address to reduce energy consumption in machine tools.
Eenergy flow visualisation
The last experience in breakdown of a 5 axis CNC machine and visualisation of energy flow in the machine tool helps 4i4 to implement this idea with some modification to this project.
This idea is developed as a project is performed in a collaboration between DTU and ETH Zurich. Based on EU legislation companies should reduce their carbon footprint and the machine tools sector is responsible to move towards energy efficient machine tools. In this project energy flow in a 5 axis machine tool is measured and visualised in order to find which component consumes more power. The experience gained from this research is
- Installing temperature, fluid, current and power sensors
- Data acquisition by LabVIEW
- Energy flow visualisation by Sankey diagram
- Proper use of documentation of machines to reduce measurement
- Verify experiment by the rule of energy conversion
The result shows the cooling system consume the main part of energy, which can be a target to address to reduce energy consumption in machine tools.
References
[1] U.S. Energy Information Administration, 1000 Independence Ave., SW, Washington, DC 20585, https://www.epa.gov
[2] CECIMO Circular Economy Report, European Association of the Machine Tool Industries (CECIMO), Edition April 2019
Reference for pictures
[1] http://www.lathes.co.uk/hamiltonmaryland/
[2] https://www.jalopyjournal.com/forum/threads/vintage-shots-from-days-gone-by.428585/page-3564
[3] https://www.nasa.gov/specials/apollo50th/missions.html
[4] https://autohatchers.wordpress.com/
