Small and medium enterprises (SMEs) may not have the maturity to put forward and unfold all the benefits from an ERP based system, a vital tool for production planning. Manufacturing ubiquitous trends, however, are more approachable to SMEs, and even the more affordable tools could be of great advantage. In this paper we propose an algorithmic framework that uses process mining tools to extract the underlying industrial process via Petri nets, and then retrieve all product tree necessary information to perform the multi-level scheduling. A faster solution decoding is proposed, for algorithms that uses random-keys. Computational experiments show that the new decoding is faster than the usual, leading to promising new paths on its future uses.

中小型企业（SME）可能尚不成熟，无法提出和发挥基于ERP的系统（生产计划的重要工具）的所有优势。但是，制造业无处不在的趋势对中小企业来说更容易接近，甚至价格更便宜的工具也可能具有很大的优势。在本文中，我们提出了一种算法框架，该算法框架使用过程挖掘工具通过Petri网提取基础工业过程，然后检索所有产品树必需的信息以执行多级调度。对于使用随机密钥的算法，提出了一种更快的解决方案解码方法。计算实验表明，新的解码比通常的解码速度更快，从而为将来的使用带来了新的希望。