Developing IIoT-enabled digital services is essential for facilitating human centered digital transformation and achieving resource-efficient production. IIoT-enabled digital services focus on providing the best possible value proposition to end users based on three main components including hardware, middleware, and visualization applications. An area of increasing interest is that of developing IIoT-enabled digital services in smart production logistics (SPL) that facilitate the delivery of material and information in manufacturing. Prior studies focusing on IIoT-enabled digital services give precedence to the location, energy consumption, and execution of material handling tasks in SPL. However, the literature neglects the importance of supporting staff responsible for maintenance of material handling equipment. Recent publications propose the use of Maintenance Opportunity Windows (MOW), yet this approach requires extensive calculations unsuitable to the dynamic environments of manufacturing. Addressing this need, the purpose of this study is to propose IIoT-enabled digital services for detecting MOW in material handling for the automotive industry. This study presents two contributions. Firstly, we draw extant knowledge about IIoT architectures in SPL to a novel context, namely that of MOW. Accordingly, this result reduces the time and resources for acquiring, processing, and identifying empty spots in MOW as compared to prior studies. Secondly, the study proposes IIoT-enabled digital services in material handling targeting maintenance staff including finding, filtering, and detecting the status of forklifts and their MOW. In doing so, the results complement existing literature about SPL targeting the autonomous coordination and scheduling of material handling. This is critical for offering digital services supporting the working needs of maintenance staff for a human centric industrial transformation.