Sixth-generation (6G) wireless networks can enable energy-efficient industrial Internet of Things (IIoT) networks. However, formidable challenges must be overcome, including stringent latency, energy efficiency, reliability requirements, and the detrimental impact of fading in wireless channels. These challenges can be addressed using dependability theory, which plays a dominant role in 6G networks as it offers a richer and more extensive performance assessment of the IIoT systems. Here, we introduce and analyze the mission Effective Energy Efficiency (mEEE). This novel dependability metric captures energy efficiency, latency, reliability, the temporal features of fading channels, and tells us how energy-efficient the system is until the first failure occurs. To illustrate the relevance of the mEEE, we consider an uplink transmission under a finite block length regime due to its ability to improve energy efficiency, maintain reliability and Quality of service (QoS), and reduce latency, where the realistic assumption of perfect channel state information (CSI) availability at the receiver is considered and there is a sporadic traffic arrival at the transmitter. Furthermore, we provide exact closed-form expressions of mission reliability (through its attributes, Mean time to first failure and failure rates) and mission effective capacity pMECq for F composite Channel by utilizing the existing framework of dependability theory. Moreover, we formulate an mEEE optimization problem with a mission reliability constraint and solve it numerically via a modified Dinkelbach algorithm because of its high performance and low complexity. Furthermore, light shadowing and less severe fading are favourable for maximum energy efficiency, particularly at ultra-reliability and longer mission durations. I. INTRODUCTION The sixth-generation (6G) networks will have a notable advantage over fifth-generation (5G) networks across various key performance indicators (KPIs) such as traffic density, delay, peak rate, connection density, mobility, spectrum efficiency, and positioning capabilities [1]. Even though the 6G networks are still developing, their superior communication capabilities will significantly accelerate the development of numerous applications, including virtual reality (VR), augmented reality (AR), UAV systems, autonomous robots, and the IoT [2]. The Industrial IoT (IIoT) being a subset of IoT connects massive devices, sensors, and manufacturing machines, which consume substantial energy. Hence, energy efficiency is considered a critical issue in many cutting-edge resource-constrained IIoT devices, such as ZigBee/LoRa-based sensors [3]. Besides, a primary challenge in IIoT networks is ensuring connectivity The authors are with the Centre for Wireless Communications (CWC),