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The purpose of a quarry is to extract rock material to deliver gravel and raw material to its customers. The products can be further processed to e.g., extract minerals such as iron or to produce cement and asphalt. These products are an important input to the construction and maintenance of road infrastructure, buildings, and more. The operation of quarry and road work sites is similar to the manufacturing industry since it contains sequential processes to produce the output product. Within the operation, there are cyclic transport activities that in general are not synchronized and controlled in real-time towards the overall throughput. This fact indicates a potential to increase productivity but also points at unsolved challenges.

This thesis investigates how Lean and systems thinking combined with real-time control and optimization technologies can be used to improve productivity and safety in the transport operation within quarry and road construction. The main contributions are the identified operational improvements, its use cases, the system design constraints, operational characteristics, and models as well as assessed impact in productivity, energy efficiency, and safety.

The results include the development and demonstration of a method based on Lean value stream mapping, for identifying wastes in sequential processes and activities including mobile earthmoving machines. Operational wastes of 33% are presented from real world operations. Related fuel savings of 42% are measured in controlled environments. Further, the thesis presents and assesses a system design for transport optimization purpose. A study of how wireless communication and vehicular ad-hoc networks (VANET) can be utilized and its performance within the quarry and road construction operation is presented. The main system requirements and constraints are identified, and the trade-offs are discussed in terms of system design with a system of systems perspective. Energy consumption models are developed for optimization purposes and the key characteristics of real world operation is identified. Finally, a prototype system has been developed and tested in controlled and operative environments. In controlled trials, a fuel reduction of 20% for individual machines was obtained using the suggested optimization technique.