## 6 Final Remarks, Implications, and Future Research  
Examining the historical progression of manufacturing system technology, three fundamental measures--quality, productivity, and cost--are commonly employed, interconnected, and integrated. However, the initial industrial revolutions predominantly prioritized measuring productivity over the other two parameters [18]. This study offers insights into assessing the current state, process control, and transitioning to Smart SPC. Building upon a model proposed by [15], a literature review helped to structure a model and define guidelines for the transition from SPC to Smart SPC. The presented model evaluates process quality concerning both product and machinery, encompassing analysis, interpretation, and decision-making for interventions and quality enhancements. The model's validation involved interviews and questionnaires to gather feedback from subject matter experts. This research makes valuable contributions to the fields of Industry 4.0, quality management, condition-based maintenance literature, and industrial management. It amalgamates quality and maintenance concepts influenced by Industry 4.0 technologies, showcasing the practicality of applying digital technologies to Smart SPC. Consequently, it advances the concept of smart manufacturing by integrating autonomous and self-adjusting control into the process. Despite studies on the fourth industrial revolution dating back to 2011, there still needs to be more potential for further research. In terms of managerial contributions, this study provides guidelines for managers to implement the Smart SPC model in the industrial sector. The model's adaptability to various contexts and types of production processes, derived from different studies and validated by specialists from diverse fields, underscores its versatility. However, adjustments are essential to align the model with the specific realities of each company. This study has limitations. Firstly, this research primarily focuses on the initial stage of implementing SSPC. Future studies could delve into the long-term implications, challenges, and benefits of sustained integration to provide a comprehensive understanding of SSPC's effectiveness over time. Additionally, the study exclusively concentrates on manufacturing activities, neglecting the service sector, where smart systems are increasingly relevant. Future investigations should explore the applicability and impact of Smart SPC in service-oriented industries, contributing to a more holistic understanding of its potential across various domains. Other fields of application of SSPC could be agro-industrial and mining activities, in which new technologies have rapidly advanced, as explored, respectively, in [60] and [61]. Moreover, the proposed model, while theoretically robust, flexible, and adaptable, requires practical validation in real-world applications to ensure its effectiveness. Subsequent research endeavors should focus on implementing the model in diverse industrial settings, allowing for the observation of its performance under varied conditions and unforeseen challenges. Future studies should also explore the model's applicability across different manufacturing contexts. It is important to evaluate the alignment of the proposed Smart SPC model with Quality 4.0 and its contribution to integrating Industry 4.0 and quality management. In accordance with findings of [18], cybersecurity remains a challenging issue. It calls for exploration of models that address data security in networked environments. While this research provides initial guidelines, further revisions and applicability analyses should be conducted in future studies. Synthesizing, the primary limitations of this study include (i) focusing only on the initial stage of the implementation of an SSPC and (ii) focusing only on manufacturing activities, excluding service, which is also a relevant realm to implement smart systems.