# Smart Manufacturing Scheduling Approaches--Systematic Review and Future Directions
## 6 Conclusions  
This work provides a literature review on smart manufacturing and, more specifically, on manufacturing scheduling. This is a very explored and discussed topic, which can hugely contribute to develop better manufacturing systems and improve the overall performance of those systems, regarding time, throughput, resources, or energetic optimization, among others. However, scheduling designing and development is not structured and harmonized between different entities, since it usually developed specifically for each case.  
Consequently, the objective of this study is twofold. On one hand, the aim was to investigate which requirements and constraints are fundamental considerations when developing scheduling solutions for industrial scenarios. This was explored in subchapter 4.1 by analyzing some reference articles and books on the topic where requirements were used more commonly and their role in the scheduling process. On the other hand, this study analyzed several articles to identify the previous requirements they considered and which objectives they tried to optimize, which can render them robust approaches to be deployed in real manufacturing situations. The result of the last point came up as table containing all the 65 analyzed articles, pointing out which requirements they considered and the most common optimization objectives.  
The results show that the vast majority of the articles only consider one or two objectives, mainly the makespan, which was found in around 65% of the articles, and tardiness related objectives, which were found in 37% of cases. It is also important to note that around 15% of the articles focused on solving energy consumption related issues, which shall be a major focus during these times of environmental awareness. Actually, environmental issues have been playing an increasingly important role in manufacturing scheduling, where studies are mainly making energy consumption assessment. However, in real manufacturing systems, depending on the case, it may be necessary to consider multiple optimization objectives. Furthermore, regarding the number of requirements considered in each study, it is possible to observe that most of the articles considered two or three requirements per case, while around 17% considered five or more constraints. It is important to understand that the more requirements considered, the more robust a scheduling solution can become, and then the more applicable it will be in real scenarios. As far as the authors know, this kind of study is not to be found in the literature.  
In the analyzed literature, no study was found describing the components of manufacturing scheduling for reference architectures. Different approaches consider different constraints, and there is not a common and uniform way of developing scheduling solutions, even though there are common points in industrial systems that may be harmonized. Having a reference for scheduling designing and development can speed up the creation of scheduling solutions and make it easier to adapt these solutions to different scenarios. Knowing that scheduling can have a direct impact on production efficiency, sustainability, and costs of manufacturing systems, it is of huge interest to conduct in-depth research on how to model smart components to optimize scheduling approaches in smart manufacturing systems. Providing a structured model that includes relevant information about the inputs of the scheduling process and the desired outputs has great relevance for the design of scheduling solutions to cope with the smart manufacturing paradigm.  
This work was supported in part by the FCT/MCTES project CESME--Collaborative & Evolvable Smart Manufacturing Ecosystem, funding PTDC/EEI-AUT/32410/2017.  
Data Availability Statement: Data sharing not applicable.  
Conflicts of Interest: The authors declare no conflict of interest.