# Production Improvement Rate with Time Series Data on Standard Time at Manufacturing Sites
## 1 Introduction  
It is an undeniable fact that a country's economic wealth and growth hinge on the prosperity of its industrial sector. However, manufacturing companies, driven by globalization, continually strive for greater competitiveness. To remain competitive on a global scale, these companies must not only develop and produce innovative, high-quality products with short lead times but also design resilient and flexible production systems that foster operational excellence. Additionally, they must engage in ongoing improvement activities to reduce lead times [1]. In today's business landscape, whether in manufacturing or services, organizations must be agile in responding systematically to customer needs [2]. Manufacturing organizations, in particular, need production strategies that align with corporate and business objectives, emphasizing the development of production systems and resources. There is also a growing focus on economic, environmental, and social sustainability, which is pushing the adoption of efficient resource utilization in production systems [3]. Therefore, it is vitalfor any organization to enhance company operations and business strategies to add value to products and improve productivity, ensuring they stay ahead of competitors [4]. Companies employ various methods to boost their competitiveness. For example, Toyota, a Japanese automobile company, introduced Lean Manufacturing (LM) or the Toyota Production System (TPS), which has been widely adopted globally due to its proven benefits, including quality improvement, cost reduction, flexibility, and rapid response [5]. However, these endeavors come with challenges, such as fierce competition, unpredictable economic conditions, and resource constraints [6]. Consequently, companies aim to refine their manufacturing methods and processes by reducing waste, a central theme in the lean methodology, to cut costs, enhance quality, increase profits, and maximize customer value through productivity enhancements [7; 8]. Increasing productivity in manufacturing is a challenge. Every manufacturing organization aspires to achieve productivity gains by reducing costs, improving quality, and delivering products to customers promptly. With the advancement of artificial intelligence (AI), achieving these objectives has become more sophisticated, owing to the availability of more precise analytics. The device manufacturing industry relies on expensive equipment for production. In a rapidly changing economy, one wants to reduce possible investments in expensive equipment and maximize the effectiveness of production. Therefore, improving manufacturing environments and increasing productivity are essential. If the results of productivity improvement initiatives can predict the capacity of future factories, guide equipment procurement, and support facility expansion, it is possible to minimize equipment investments and prepare for future productivity improvements based on actual performance. Hence, even though there are various productivity improvement activities, quantifying productivity gains in terms of production time is crucial for equipment capacity predictions. Production time, as a quantifiable result of productivity improvement, serves as a valuable indicator. In manufacturing, reducing production time directly contributes to productivity enhancement. We attempted to calculate the productivity improvement rate for production time, aiming to use it for predicting future production capacity based on production volume classification. Productivity improvement activities can be accomplished in the following ways:  
* Improving process efficiency: How to improve the process efficiency of your instruction line (analyzing work processes, improving bottlenecks, eliminating waste, etc.). * Automation: How to introduce automation technology into your production system to automate production processes, increase sales hours, reduce unnecessary labor, and enable batch production.