## 1 Introduction  
The quest to improve productivity in today's competitive global environment has led to a need for rigorously defined performance measurement systems for production processes that indicate production losses and areas of process improvement. This situation requires additional well-defined performance metrics that consider three important factors: equipment availability, performance, and quality. Performance measures can be obtained through a combination of various operation measurements. To measure the overall operation metric, Overall equipment equipment effectiveness (OEE) as a key performance indicator (KPI) was introduced by [PERSON] and applied to measure equipment productivity [1; 2; 3; 4]. OEE is increasingly used in the industry as an indicator and driver for controlling and monitoring equipment performance, as well as an indicator and driver for process and performance improvement. The relationship between availability, performance, and quality established in OEE is key to its usefulness and has come to be used as a metric in business decision-making processes [5; 6]. The main advantage of OEE over other KPIs is in combining three separate elements into a single number that is perceived as an overall performance indicator. This indicator is useful because it consolidates overall operation metrics and is simple and clear in facilitating the identification of areas of potential improvement. OEE research is prevalent in a variety of manufacturing sectors such as aerospace, automotive, and paper, and is used to measure mining equipment effectiveness [7; 8; 9; 10]. The articles contain scientific and practical content regarding the OEE concept, but implementation in the mining transportation context has been little addressed. We studied the article on the OEE concept applied to mining equipment; however, this concept used traditional OEE [7]. Problems occurred when traditional OEE was used in the mining environment, because some elements, such as quality rate, were designed for the manufacturing environment. This element must be modified to meet the unique nature of mining. It is also important to find and use the appropriate tools to measure the effectiveness of transportation processes and to eliminate those processes that do not add value [11]. OEE has therefore been developed as an effective measurement indicator in the road transportation sector [12; 13; 14; 15]. However, these concepts do not apply to mining transportation since they were developed for urban freight transportation applications. The factors that build the indicators do not represent the mining transportation process, since they use on-time delivery, clients not served, excess distance, product defect, faulty delivery, traffic jams, etc., as transportation losses. These kinds of losses are designed for urban cargo transportation, not for mining. Urban freight transportation has multiple destinations, carries various goods, serves various customers, and has a more predictable working environment. Cargo transport is focused on service level. Mining transportation has unique characteristics since it exists in a physically challenging environment, an inherently variable working environment that is impacted by weather and widespread mining locations [16; 17]. Trucks transport coal only in bulk to a specific destination. The most critical challenges for mining equipment are utilization, productivity, and operation safety. Therefore, the objective of this paper is to (1) establish a new metric to measure the overall effectiveness of coal mining transportation; (2) validate the proposed metric; and (3) apply this metric to the coal-hauling fleet transporting coal from pit to port in a coal-mining project in Indonesia. To achieve this goal, a new metric will be developed using a mixed method approach with a three-round Delphi study to propose a new consolidated metric quantifying the effectiveness of the coal transportation process, and then apply it to measure the effectiveness of the coal-hauling process.