The present invention relates to a system and a method for handling a production disturbance/opportunity event in a production execution system.
In the world of process automation and process monitoring standard automation systems for controlling the widest conceivable variety of machines and plants are state of the art. Such technology covers in particular a broad range of products which are offered by the Siemens Corp. under its SIMATIC® product family with the field of manufacturing execution systems (MES). An extensive line of products for solving the technical tasks in question such as counting, measuring, positioning, motion control, closed-loop control and cam control enhance the performance capabilities of appropriate process controllers. A variety of configurations enable the implementation of flexible machine concepts.
In this context a broad range of IT solutions exist to connect the actual hardware close to the technical and/or logistical process to the application layer of the client driving the installation. Manufacturing execution systems have therefore been developed to meet all of the requirements of a service oriented architecture (SOA) to integrate seamless into a totally integrated automation (TIA). A plug & play architecture, in which the individual functions can be easily combined and configured with each other thereby forms the basis for this success thereby simplifying the complex structures of controlling a manufacturing plant or the like.
These demands very often require in the backbone rather complicated and sophisticated software solutions which enable the approach of totally integrated automation. In view of this, the software engineers very often use production moduler to define the plant model and its standard operating procedures and create the respective new software by means of a high level graphical language which identifies the workflow of activities within the software. Subsequently, this string/term of high level graphical language is translated into a client based software language executable on the machine language level. This translation requires tremendous efforts in programming and need serious testing to check whether the translated program behaves the same as the original string/term of the high level graphical language.
Within this MES environment a software for a detailed production scheduling (PDS) is provide which concerns the sequencing and the timing of production operations on all manufacturing resources. This software has the aim to create an executable and optimized production schedule that will be dispatched in production to be executed. Before the scheduling will be computed, the PDS software needs to feeded with the main input from a plant database such as:                a) the plant logical layout and material flow constraints;        b) the equipment and personnel standard production rates;        c) the availability, the calendar and the status for the equipment and personnel;        d) knowledge on the way of production (recipes, routings, etc.), process and business constraints.        
Together with this information the PDS software builds its internal model of the plant and of the production process within this plant. Subsequently, by applying the scheduling algorithms to this internal plant model of the plant's resources and production process, the PDS software computes an executable and optimized production schedule which does not violate any physical, logistical and/or business constraints and which emphazises eventually an optimal respect of the manufacturing performances. The basic assumption of this computation lays in the plant and the production process model known at the beginning of the computation and at each moment of the scheduling time horizon.
Unfortunately, during the actual execution of the production schedule, only in an imaginary factory everything will work as it is assumed by the schedule. What happens in real environment is well known to any production manager: after the production schedule has been released for execution, unpredictable errors and failures occurs, such as:                a) machine breakdowns;        b) slowdown of production rates;        c) quality problems on some material components delivered to production; and        d) operators absenteeism.        
For these reasons the basic assumption of deterministic and known plant conditions the production schedule was based on are no longer valid at execution time. This divergence could render the released production schedule as being not executable any longer or not as good as it was planned. In this case, these unpredictable events are called production disturbances (e.g. failure of a machine while it was working according to the schedule). On the other hand, there exist circumstances under which changes in plant condition could be favorable, such as a machine producing faster than the standard average production rate is planned to replace a slower one or after failure of a machine another machine can be allocated to this production chain. These also unpredictable events are hereinafter called production opportunities. In order to take advantage of such a production opportunity, the production schedule and/or other plant conditions should be modified as well.