New technologies have a great influence on the production process in modern factories. Introducing new techniques and methods is crucial to optimize and enhance the working of factories. However, ensuring a reliable and correct integration requires complete evaluation and assessment. In this thesis I utilize RFID systems and image processing to develop and implement real time solutions to enhance and optimize the production and assembly processes. Solutions include: RFID based CEP to detect production error, image processing based errors detection to detect post-assembly errors, and RFID based HCI to help workers in assembling products. Errors that are detected using RFID are: sequence errors, synchronization errors, pre-assembly order errors, part-product mismatch error, and missing parts errors. Errors that are detected using image processing are: incorrect part position errors and missing parts errors. RFID based HCI consists of a tool to help workers at assembly points to correctly assemble parts to their products using visual instruction. I have constructed prototypes for all the solutions. As well, I have deployed them in the Lernfabrik(learning factory) which is a real manufacturing environment for practising the production and assembly processes for trainees and students. Under the optimal settings of the RFID readers and tags, the system detects all types of errors reliably in real time. The image processing algorithm detects errors with 100% accuracy in real and normal lighting conditions of the Lernfabrik.