In today's digital age, manufacturing companies generate a vast amount of data, from the shop floor to the supply chain. However, collecting and analyzing this data can be a daunting task, especially for businesses lacking a solid data foundation. FojiSoft has developed a powerful cloud platform that can handle data at scale, enabling more advanced analytics use cases and accelerated decision-making. In this blog post, we will explore how FojiSoft's manufacturing data platform facilitates IT/OT convergence with a precise asset model and plant hierarchy established in the cloud, coupled with AI/ML-based analytics capabilities. Let's dive in and discover how FojiSoft's technology can help businesses unlock the power of their data.
Data analytics has become increasingly important for manufacturers in recent years. By leveraging data, manufacturers can optimize their operations, improve product quality, and reduce costs. However, many manufacturers struggle to harness the full potential of their data due to challenges associated with aggregating data from disparate sources.
In the past, manufacturers typically relied on separate information technology (IT) and operational technology (OT) systems, resulting in siloed data. With the rise of Industry 4.0 and the Internet of Things (IoT), it has become increasingly important to integrate IT and OT data to achieve a complete view of manufacturing operations. By aggregating data from both IT and OT sources, manufacturers can gain insights into their entire production process, from raw materials to finished goods. This allows them to make more informed decisions, optimize processes, and ultimately improve their bottom line.
The Four Categories of Data Analytics in the Manufacturing Industry
FojiSoft is a smart manufacturing software company that offers various solutions and accelerators for data analytics in the manufacturing industry. Data analytics can be broadly classified into four categories, all of which leverage artificial intelligence (AI) and machine learning (ML) for deriving insights. These categories include:
- Descriptive Analytics: This category of analytics provides information on "what" is happening at a manufacturing facility, such as manufacturing KPIs like OEE and cycle time.
- Diagnostic Analytics: This category of analytics helps determine "why" an event occurred, such as why unplanned machine downtime occurred.
- Predictive Analytics: This category of analytics involves detecting anomalies and predicting an event before it occurs, such as predicting equipment failure or a drop in quality before it happens.
- Prescriptive Analytics: This category of analytics combines data, AI models, and business rules to generate recommendations for decision-makers, helping organizations identify the best course of action to take in every situation, such as preventing equipment failure by providing recommendations to schedule maintenance and order spare parts.
Examples of Value Created
FojiSoft offers several solutions and accelerators that utilize its Cloud offering for data specifically for Manufacturing, including the following:
- Cycle Time Analytics: Cycle time refers to the time it takes for a machine or process to complete a single production cycle. FojiSoft offers solutions ranging from descriptive to predictive analytics to help customers analyze and optimize cycle time metrics and identify bottlenecks and inefficiencies in the production process.
- Yield: Yield is the proportion of product that is successfully produced in relation to the total amount of raw materials used in the production process. FojiSoft offers solutions utilizing data- and AI-driven insights to accelerate RCA, reduce and/or eliminate bottlenecks and quality issues to improve yield overall.
- Overall Equipment Effectiveness (OEE): OEE is a metric used to measure the efficiency of a manufacturing process or production line. FojiSoft offers solutions that provide OEE insights and RCA tools to understand a drop in OEE and correlate that back to individual constituent elements to better understand the issue.
- Predictive Maintenance: FojiSoft leverages AI/ML capabilities to build predictive maintenance applications that predict when equipment or machines are likely to fail or require maintenance, minimizing the risk of unplanned downtime and improving the overall reliability and efficiency of the production process.
- Energy Optimization: At FojiSoft, we optimize energy consumption at manufacturing facilities by contextualizing energy data with respect to production line, machine, shift, operator, and products. We help customers reduce peak loads by understanding peak load characteristics.
