Author ORCID Identifier

Date Available


Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation




Mining Engineering

First Advisor

Dr. Steven Schafrik

Second Advisor

Dr. Zach Agioutantis


Roof bolting is a critical operation in ensuring the safety and stability of underground mines by securing the roof strata with bolts. The process involves moving and manipulating heavy tools while being vigilant about the safety of the area. During the installation of roof bolts, operators are exposed to hazardous conditions due to challenging working conditions in underground mines, extensive working hours, and demanding shift schedules leading to personnel fatigue and influencing operators to take shortcuts that may increase the risk of injuries and fatal accidents. The successful completion of roof bolting tasks depends heavily on operator judgment and experience to perform these tasks. To mitigate the occupational hazards inherent in roof bolting operations, a six-axis ABB IRB 1600 robotic arm was integrated into the roof bolter machine to imitate human functions during the roof bolting operation.

The integration process involves selecting a suitable robot that can perform human activities and has the potential to handle the tasks at hand. The ultimate goal of implementing the robotic system into the roof bolter machine is to minimize human involvement during the roof bolting operation by converting the machine from manual operations to a partially automated roof bolter machine. The integration enhances the safety of personnel by moving humans away from the face where roof bolting takes place to a safe distance. The operator is then assigned a new role to control and supervise all the operational tasks of the automated roof bolting operation via a human-machine interface (HMI).

During the laboratory testing of the automation process, the robotic arm cooperates with some novel specialized technologies to imitate human activities during roof bolting operations. The developed systems include the plate feeder, the bolt feeder, and the wrench. These systems were built to support automation and minimize human intervention during roof bolting operations. These components were linked to the Programmable Logic Controller (PLC) and controlled by the HMI touchpad. An HMI was developed for the operator to control and monitor the automated process away from the active face.

This study establishes robust communication paths among all the components. The design communication network links the robotic arm and other components of the roof bolter machine, leading to a smooth and sequential roof bolting process. The EtherNet/IP protocol is used to pass messages between the components of the automated roof bolter machine through a Controller Area Network (CAN) bus device installed to enable communication using CAN protocols. Establishing a robust communication network between the components prevents collision and manages the movement of the robotic arm and other developed automated systems during the bolting process.

The outcome of the study shows that the robotic arm has the potential to mimic human activities during the roof bolting operation by performing bolt grasping, holding, lifting, placing, and removal of drill steels during the roof bolting operations. As a result, humans can be moved away from hazardous areas to a safe location and control the roof bolting operation through an Human Machine Interface (HMI) touchpad. The HMI controls the bolting process with start and stop buttons from the subroutine of all the components to perform the roof bolting operation. These buttons enable the operator to stop the operation in the event of unsafe acts.

Digital Object Identifier (DOI)

Funding Information

This study was sponsored by the Alpha Foundation (Grant AFC820-68) - Roof Bolting Module Automation for Enhancing Miner Safety. The views, opinions and recommendation expressed herein are solely those of the authors and do not imply any endorsement by the ALPHA FOUNDATION, its Directors and Staff (2019 - 2023).

Grant AFC820-68