# Digital Transformation of Production Planning and Control in Manufacturing SMEs-The Mold Shop Case
## 5 Conclusions  
This work demonstrates a feasible way for manufacturing SMEs to adopt digital manufacturing technologies that can bring benefits to their processes. Addressing real industrial cases helps understand the real-world implications and thus provides practical approaches to resolve them. The proposed technologies facilitate the digitization and use of production and operational resource data within a mold production environment. The DT project has brought improvements in capturing the production activity, both by the operators and the machines, offering the capability to the production manager for up-to-date information on the work-in-progress on the factory floor as well as the capability to schedule and re-schedule the production to address disturbances in the environment. Moreover, at the technical level, the DT project has shown that open-source solutions used from the FIWARE community are mature ones which can be successfully integrated into production environments. At an organizational level, the active engagement of the shop-floor personnel and engineering department from the early phases plays a crucial role in user acceptance. Moreover, incremental deployment of the solution relieves the frustration of changing business processes from the management personnel as it allows for smooth communication of the changes to the shop-floor personnel. As the next steps in the DT project are under discussion, it is envisaged to enrich the functionality of the existing apps. The Production Schedule app should be enriched with functionality that will allow users to perform \"quick\" plans based on input scenarios for estimating capacity and capabilities of the production to manage it. The Shopfloor Status app will be enriched with additional views i.e., per department and WorkCentre as well as with visual indication of production status (i.e., ahead green light, behind orange light, overdue red light). \begin{table}
\begin{tabular}{c c c} \hline \hline Major Obstacles & \(\bullet\) & No major obstacle has been identified. \\ \hline Key Learning & \(\bullet\) & From a technical and software development perspective, it was clear to the development team that the FIWARE components used (ORION and IDAS IoTAgent) are mature solutions with straightforward integration steps. \\  & \(\bullet\) & Moreover, the execution performance of the FIWARE tools was also within the expectation with no major issues identified in aspects like response times or stability. \\ \hline Best Practices & \(\bullet\) & Active engagement of the shop-floor personnel and engineering department in the design process of the user interfaces from the early phases plays a crucial role in the user acceptance. \\  & \(\bullet\) & Incremental deployment of the solution relieves managerial/engineering personnel of the frustration of changing business processes radically and communicating the radical change to the shop-floor personnel. \\ Best Practices & \(\bullet\) & 1 st installation we introduced the shopfloor screens to operators allowing them to choose the task/part and machine/process at will, without the restriction of following a specific production schedule. \\  & \(\bullet\) & 2 nd installation we introduced the rules to be followed and the application feedback which would guide the operators in choosing the “planned” task/part for a predetermined process/machine. \\ \hline \hline \end{tabular}
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Table 4: Experiment with qualitative analysis from a technical point of view. **Author Contributions:** Conceptualization, K.A. ; methodology, K.A., N.N. and E.X. ; software, E.X. ; validation, K.A. and E.X. ; writing--review and editing, K.A., N.N. and E.X. ; supervision, K.A. All authors have read and agreed to the published version of the manuscript. **Funding:** This work has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 873086. **Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.