Workload control (WLC) is a lean oriented system that reduces queues and waiting times, by imposing a cap to the workload released to the shop floor. Unfortunately, WLC performance does not systematically outperform that of push operating systems, with undersaturated utilizations levels and optimized dispatching rules. To address this issue, many scientific works made use of complex job-release mechanisms and sophisticated dispatching rules, but this makes WLC too complicated for industrial applications. So, in this study, we propose a complementary approach. At first, to reduce queuing time variability, we introduce a simple WLC system; next we integrate it with a predictive tool that, based on the system state, can accurately forecast the total time needed to manufacture and deliver a job. Due to the non-linearity among dependent and independent variables, forecasts are made using a multi-layer-perceptron; yet, to have a comparison, the effectiveness of both linear and non-linear multi regression model has been tested too. Anyhow, if due dates are endogenous (i.e. set by the manufacturer), they can be directly bound to this internal estimate. Conversely, if they are exogenous (i.e. set by the customer), this approach may not be enough to minimize the percentage of tardy jobs. So, we also propose a negotiation scheme, which can be used to extend exogenous due dates considered too tight, with respect to the internal estimate. This is the main contribution of the paper, as it makes the forecasting approach truly useful in many industrial applications. To test our approach, we simulated a 6-machines job-shop controlled with WLC and equipped with the proposed forecasting system. Obtained performances, namely WIP levels, percentage of tardy jobs and negotiated due dates, were compared with those of a set classical benchmark, and demonstrated the robustness and the quality of our approach, which ensures minimal delays.

工作负载控制（WLC）是一种精益的系统，通过对释放到车间的工作负载施加上限，从而减少了队列和等待时间。不幸的是，WLC的性能并没有在系统利用率方面超过推式操作系统，因为利用率水平不足，调度规则也得到了优化。为了解决这个问题，许多科学著作都使用了复杂的作业发布机制和复杂的调度规则，但这使得WLC对于工业应用而言过于复杂。因此，在这项研究中，我们提出了一种补充方法。首先，为了减少排队时间的可变性，我们引入了一个简单的WLC系统。接下来，我们将其与预测工具集成在一起，该预测工具可以基于系统状态准确预测制造和交付工作所需的总时间。由于因变量和自变量之间是非线性的，因此使用多层感知器进行预测。为了进行比较，还测试了线性和非线性多元回归模型的有效性。无论如何，如果到期日期是内生的（即由制造商设定），则可以将其直接绑定到此内部估算。相反，如果它们是外生的（即由客户设置），则此方法可能不足以使迟到的工作所占的百分比最小化。因此，我们还提出了一个协商方案，该方案可用于扩展内部评估相对过紧的外部到期日。这是本文的主要贡献，因为它使预测方法在许多工业应用中真正有用。为了测试我们的方法，我们模拟了由WLC控制并配备了建议的预测系统的6台机器的车间。将获得的性能（即在制品水平，工作迟缓的百分比和协商的到期日期）与设定的经典基准进行比较，并证明了我们的方法的鲁棒性和质量，可确保最小的延迟。