مقاله انگلیسی رایگان در مورد سیستم های اجرایی تولید هوشمند برای شرکت ها – الزویر 2018

3. Key Services

3.1. RFID middlewar

e RFID middleware is one of the most important features of the MES. It is responsible for services that manage raw data as well as inter-device communication. Two key functionalities are associated with this service – data collection/acquisition and maintenance management. The latter will not be discussed in this paper as it is not yet implemented. Data collection is essential to the proper implementation of manufacturing execution systems. Traditional paper-based style of operations, are often error prone and unable to cope with dynamic shop-floors, among other things. These problems arise mainly due to the untimely gathering of information which can be achieved through proper deployment of RFID enabled smart devices such as workers, machines and resources. Figure 1 shows how the smartphone app bridges the connection gap between the RFID devices and the cloud MES. Appropriate usage of this at key stages, would enable data to be frequently updated, allowing location and status, among other things, to be known. Once this data is collected, it is organized into information that can be used so that appropriate feedback can be sent back. Due to the nature of RFID many security measures need to be put in place to prevent the loss of any data

3.2. Planning and scheduling service

Planning and scheduling services provide proper guidance in the optimization of processes and operations. This service addresses two functionalities – process management and, operations and detailed scheduling. Process management is the method used to define the process that raw material would have to undergo as it becomes the final product. Whereas operation and detailed scheduling is used to determine when and for how long the process should occur. When jobs are registered, managers would input information such as priority, importance, machining process to use, etc. The middleware service would then collect and organize this data so that an optimal method can be computed. This would be formulated for each instance using a set of rules or logic governed by the input parameters as well as real-time data. Once the process method is known, the operations and detailed scheduling can be generated and sent to the workers. This would take into account constraints, such as due dates, placed by clients or otherwise and automatically adjust current and future schedules