# A Dynamic Adjusted Aggregate Load Method to Support Workload Control Policies
## 1 Introduction  
Workload control (WLC) approaches are widely used in the case of small and medium enterprises with make to order (MTO) production systems. Some examples in the MTO context are companies that provide subcontracting for several customers, such as aerospace, commercial, textile and food industries. In the production of aluminum rails, the enterprises operate with a lot of rails with the MTO approach. Other studies have investigated the potential application in semiconductor industries [1; 2; 3; 4]. The WLC is an order release mechanism for controlling work in process (WIP) and flow time using a pre-shop pool where the jobs wait until the conditions to enter are verified. The input of a new order is allowable, considering the workload limits of the workstations (norm limit). This allows maintaining an optimal level of WIP, reducing the shop floor flow time and queue lengths in front of the work centers. The main benefit of the WLC approach is to reduce the impact of the variations of the incoming orders on shop floor performance [5]. [PERSON] et al. [6] considered three main decisions related to workload control (the acceptance/rejection order is not considered in this paper). The first decision is the release decision of the orders that wait in the pre-shop pool of the manufacturing system [7]: the approaches proposed in the literature are periodic and continuous. The continuous release method is more complex to introduce, but this approach can lead to better results [8]. The second decision concerns the priority dispatching rule for the orders in pre-shop. Several rules can be used, such as the earliest due date, shortest process time, etc. [9]. Then, the order with the highest priority can be released if the norm of the workstations (or the bottleneck) is lower than a defined limit. In the literature, the norm of all workstations or the norm of only the bottleneck workstation [10] was considered. The third decision concerns how the aggregate workload is computed. The more used approach is the adjusted aggregate load method [11] that consideredthe ranked visit of the jobs to the workstations. Processing time as a contribution to the workload is reduced proportionally to the position of the workstation in the routing of the job. The research proposed in this paper concerns the study of a job shop under a continuous workload control method. The main focus of the research concerns the computation of the aggregate workload of the manufacturing system used to define the norm level for the release of jobs. The aggregate workload computation proposed is a dynamic computation that is updated after each operation performed by a workstation. Then, the order release in the pre-shop is related to a continuous updating of the workload information. The development of the digital manufacturing concept enables the potential real industrial application of the proposed method. Internet of things (IoT) enables integration of the manufacturing resources into the information network [12], to make the information easy in real-time of the resources. Therefore, the continuous update of the adjusted aggregate workload can be introduced in real industrial applications with digital tools. This research used simulation to assess the proposed model performance compared with the classical adjusted workload computation proposed in the literature. Moreover, robustness is evaluated, considering different dispatching rules of the pre-shop queue, workload norm evaluation and job release rules. The simulation model developed allows study of a wider range of performance measures than the works proposed in the literature. The remainder of this paper is organized as follows. Section 2 provides an overview of the literature focused on workload computation in continuous workload control models. Section 3 describes the reference context of the study proposed and the proposed workload computation method.