opportunities and hallenges for agv technology in material ... · a sophisticated simulation model...
TRANSCRIPT
AGV — Automated Guided Vehicle
An AGV is a driverless industrial vehicle used in man-
facturing plants and warehouses to transport material.
The first AGV was introduced in 1953 using tactile safety
sensors and simple wire guidance. Since the mid-1990s,
the industry has boomed, now offering multiple navi-
gation technologies and sophisticated software controls.
Objective
Examine the available and relevant AGV technology
Identify the opportunities and challenges to
implementing AGVs for material supply on the
manufacturing floor in Volvo Cars Final Assembly.
Author:
Sten Björn ANDERSSON
Academic Supervisor EPFL: Industry Supervisor:
Prof. Philippe Wieser Kristoffer Mann, Volvo Cars
Opportunities and Challenges
for AGV-Technology in Material Supply
for Automotive Final Assembly
Methodology Industry 4.0
Manufacturing industries are moving towards
increased automation and digitalisation under
the Industry 4.0 paradigm with more decentrali-
sed control, modularity and real-time capabili-
ties.
Fig. 3 a-e: Navigation Technologies [Top-to-bottom, left-to-right] 3a: Inductive wire, 3b: Magnetic tape, 3c: Magnetic spot,
3d: laser navigation using artificial landmarks, 3e: natural landmark / contour laser navigation (Transbotics.com, 2018)
Whilst AGVs currently can be considered
”intelligent but not autonomous”. AGVs are
currently becoming increasingly autonomous enabling the vehicle fleet to reconfigure
to the needs of the production system. The future of the AGV industry is conjectured to
be enhancing the vehicle and fleet ability to share traffic information and redistribute
transportation assignments to ultimately provide flexibility and logistical efficiency.
Fig 1: Smart Connected AGVs (Sickinsight-online.com, 2018)
Fig. 4e: Underride AGV configuration (Savant Automation, 2018)
Fig. 4b: Piggyback (conveyor-loaded) AGV
(Hilelectro.net, 2018) Fig. 4a: Forklift AGV (Rocla, 2018)
Fig. 4c: Towing Tractor AGV (Robotic Automation, 2018)
Fig. 4d: Underride AGV (Wiscolift, 2018)
The most common AGV vehicle types
Acknowledgements:
Volvo Cars: Manufacturing Engineering Department
Mats Hultman, Veikko Turunen, Morgan Ericsson,
Ola Fogelmark & Jonathan Legat-Odin, Volvo Cars.
Yang Yaqing, Lynk & Co. Jakob Dannemark, AGVE
Pär Knutsson, Jernbro. FlexSim
Fig. 2 a [top]: Protective Fields of a Safety Sensor
Fig. 2b [bottom]: Laser Safety Sensor (Ullrich, p.120, 2015)
Energy Supply:
Virtually all indoor AGVs are electrified. The most common solution for logistic
AGVs, as opposed to assembly-fixture AGVs, is a battery solution. The battery can
either be replaced or charged on-board.
Manual battery exchange: suitable for smaller fleets in continuous operation.
Automatic battery exchange: suitable for larger fleets in continuous operation.
Automatic on-board charge: scheduled charging, suitable for cyclic applications
Opportunity on-board charge: non-scheduled charging, suitable for appli-
cations with varying workload.
Safety:
Personal detection: the vehicle must be
able to detect pedestrians and plant infra-
structure and avoid collision by braking.
Laser sensors, see Fig. 2b, is the industry-
standard with different protective fields
set as shown in Fig. 2a.
Industry standards limit the operating
speed to 1-2 m/s. The AGV path should
also feature a 0.5 m margin on either side.
Sten Björn ANDERSSON Master Thesis MSc Mechanical Engineering
Navigation
Fixed-path navigation
- Inductive wire
- Magnetic/Optical track
Open-path navigation
- Magnetic Spot
- Laser (Artificial landmark)
- Natural / Contour laser
Impact of AGVs
Improved labour efficiency
Improved plant safety
Real-time tracking of material
Reduced damaged goods
Improved energy efficiency
Longer lifetime than manual
trucks
Space-efficient
Significant initial investment
Less flexible compared to
manual vehicles
Slower speed and loading
compared to manual trucks
Sources Images:
Hilectro.net. (2018). Piggyback AGV-Piggyback AGV. [online] Available at: http://www.hilectro.net/Piggyback%20AGV_149_745.html [Accessed 9 Aug. 2018].
Roboticautomation.com.au. (2018). ECO Z Towing AGV | Robotic Automation. [online] Available at: http://www.roboticautomation.com.au/agvs/industrial-agvs/dedicated-agvs-
eco-series/eco-z-towing-agv [Accessed 12 Aug. 2018].
Rocla. (2018). Fork Over Lift AGV. [online] Available at: https://www.rocla-agv.com/en/products/fork-over-lift-agv [Accessed 7 Aug. 2018].
Savant Automation (2018). [online] Agvsystems.com. Available at: http://www.agvsystems.com/wp-content/uploads/2018/07/AGV-AGC_Model_DC10_180701.pdf
[Accessed 3 Jun. 2018].
Sick.com. (2018). Protecting automated guided vehicles (AGV) | SICK. [online] Available at: https://www.sick.com/us/en/industries/industrial-vehicles/automated-guided-systems/
automated-guided-vehicles/protecting/protecting-automated-guided-vehicles-agv/c/p360745 [Accessed 15 Jul. 2018].
Sickinsight-online.com. (2018). Thinking ahead intelligently. [online] Available at: http://www.sickinsight-online.com/thinking-ahead-intelligently/ [Accessed 16 Jul. 2018].
Transbotics.com. (2018). Guidance and Navigation for AGV and AGC automatic guided vehicle manufacturer. [online] Available at: https://www.transbotics.com/learning-center/
guidance-navigation [Accessed 10 Aug. 2018].
Ullrich, G. (2015) Automated Guided Vehicle Systems: A Primer with Practical Applications. 2nd ed.
Wiscolift (2018). AGV, Model E3500 Tunnel Style Automated Guided Vehicle. [online] WiscoLift, Inc. Available at: https://www.wiscolift.com/products/e3500-tunnel-style-
automated-guided-vehicle [Accessed 12 Aug. 2018].
Fig. 5: Simulation Engine Delivery using Flexsim
Fig. 7: Process Plan Dashboard Delivery
Fig. 6: Process Plan Windshield Delivery
Conclusion:
It is recommended to use open-path navigation as it permits smaller modifications to
the route network to be done virtually. The most relevant technologies were judged to
be laser navigation, using artificial or natural landmarks, and magnetic spot navigation
because of their high reliability and flexibility. These technologies could advantageously
be used in hybrid as their flaws complement each other.
The most relevant energy supply option was seen to be automatic or opportunity on-
board charging to eliminate manual intervention and take advantage of often naturally
occuring idle time.
The main opportunities were identified as reducing labour costs and improving plant
safety. The key challenges were identified as operating in an environment shared with
manual traffic, identifying suitable processes, where de-facto rationalisation can be
made, and setting an adequate level of automation
Case Studies & Simulation:
3 specific case studies were selected and analysed further including the supply of
windshields, dashboards and engines.
A sophisticated simulation model was developed, using Flexsim and their AGV-module,
to model the engine material flow. This was done to discover how AGV application
could handle a varying workloads using a simple dispatching algorithm essentially assig-
ning transportation assignments in the order of appearance. The conclusion drawn
from this simulation is that for varying workloads the AGV system must be granted a
maximum lead-time.
Moreover, it was concluded that for certain processes some modification to exisiting
loading and unloading station layout configuration may be required.
Based on the case studies, the conclusion was made that it should (in select processes)
be possible to rationalise one manual truckdriver with 2-3 AGVs.
Based on the site visits, interviews and case studies, it was estimated that an AGV-
system could be implemented with the initial investment offset by the reduced labour
cost in 3-4 years.
Logistics, Economy and Management Chair (LEM)