Operators in industrial manufacturing environments are under pressure to cope with the ever increasing flexibility and complexity of work. Transitioning towards data-driven smart manufacturing environments in the context of Industry 4.0 with wearable technologies and sensors brings the opportunity to (1) use the recorded data to deliver timely assistance to the operator and (2) employ it in retrospective for work process optimisation. Despite these clear opportunities challenges are raised concerning the perceived threats of the usage of the data that outweigh the perceived benefits. Thus, it is paramount to strongly consider privacy concerns when designing a system for a smart manufacturing environments from the onset rather than an afterthought. This paper presents a trust and privacy framework to address these challenges by facilitating the understanding of the role of trust and privacy in complex smart manufacturing systems. The framework is instantiated in the context of a smart manufacturing system developed in the EU H2020 HUMAN project and evaluated in three studies towards its perceived usefulness and its impact on the privacy awareness in a concrete smart manufacturing application scenario. The evaluation results show that the framework helps to structure and understand the data-flow in a smart manufacturing scenario from a privacy perspective.