Navigating the path to optimal OEE
For factory operations leaders—COOs, Manufacturing Directors, and Factory Managers—improving production efficiency is a constant challenge. The stakes are high: every minute of unplanned downtime can cost up to $22,000, and even a small improvement in Overall Equipment Effectiveness (OEE) can translate into significant financial gains. Yet, with many options to consider, how do you decide the best path forward?
This blog explores the common challenges in factory operations, evaluates the available options for efficiency improvement, and introduces a new AI technology that should be on your radar.
Understanding the challenges in factory operations
Factory operations are fraught with challenges that can hinder efficiency and negatively impact OEE. Some of the most common issues include:
- Unexplained downtime: Downtime events can occur unexpectedly and last anywhere from a few minutes to several hours. These events are often difficult to diagnose, leading to significant production losses and operational disruptions.
- Wastage: Wastage can occur at various stages of production, from raw materials to finished products. Identifying the root cause of wastage is crucial for improving efficiency and reducing costs.
- Labour efficiency: Ensuring that Standard Operating Procedures (SOPs) are followed, and that labour is utilized efficiently is an ongoing challenge. Non-compliance with SOPs can lead to inefficiencies, quality issues, and increased costs.
- Quality inconsistencies: Maintaining high-quality standards is a top priority for factory operations, but inconsistencies can arise due to a lack of real-time oversight and data-driven decision-making.
- Retrospective reporting: Many factories still rely on manual data capture and retrospective reporting, which can be error-prone and lead to delays in identifying and addressing issues.
Exploring your options for efficiency improvement
Given these challenges, factory operations leaders have several factors to consider when looking to improve efficiency and boost OEE. There are several options, each with its advantages and disadvantages. It’s important to carefully evaluate which approach best suits your specific needs.
- Hire more management or supervision
- Pros: Additional management or supervision can help ensure that production processes are followed correctly and that any issues are quickly identified and addressed. Good management is essential for maintaining high standards and ensuring that production runs smoothly.
- Cons: While additional supervision can be beneficial, it’s not always a scalable solution. Factory managers can’t see and address every problem all the time and are often challenged by ongoing firefighting, leaving little time for data analysis and strategic decision-making. Moreover, adding more management layers can increase operational costs without necessarily addressing the root causes of inefficiency.
- Improve existing manual processes
- Pros: Improving manual processes can lead to immediate gains in efficiency. Streamlining workflows, reducing unnecessary steps, and standardizing procedures can help ensure that production is as efficient as possible.
- Cons: Manual process improvements are often limited by the quality of data available. Without reliable, real-time data, it’s difficult to identify where improvements are needed or measure their impact. A data-driven approach is essential for sustained improvements.
- Upgrade existing systems
- Pros: Upgrading existing systems, such as Manufacturing Execution Systems (MES), Enterprise Resource Planning (ERP) systems, or IoT sensors, can enhance data collection and analysis, leading to better decision-making and improved efficiency.
- Cons: System upgrades can be costly, time-consuming, and even interrupt production, causing further downtime. Moreover, existing and longstanding providers may have foundational technology limitations that restrict the potential value of these upgrades. It’s important to evaluate whether the benefits of upgrading justify the investment, especially if the technology is nearing obsolescence.
- Invest in traditional technology
- Pros: Traditional solutions like CMMS (Computerized Maintenance Management Systems), MES, ERP add-ons, and IoT sensors are well-established and offer a range of functionalities to improve production efficiency.
- Cons: While these systems can provide valuable data, they often come with high total costs of ownership, including licensing, maintenance, and support costs. Additionally, these systems may require significant internal resources for integration and administration. It’s important to weigh the benefits against the potential costs and resource strain.
- Invest in AI
- Pros: AI holds the key to optimal production efficiency outcomes. Manufacturers who embrace AI adoption as a strategic imperative will be more efficient and competitive in challenging market conditions. Visual AI, a subset of AI, offers accessible AI at low risk and with minimal barriers to adoption. Visual AI specialists develop AI models that track and provide solutions for improving OEE. By using existing camera infrastructure, Visual AI provides real-time insights into production processes, enabling proactive decision-making and reducing downtime.
- Cons: Understanding different AI options is crucial. Not all AI solutions are created equal, and some may require significant data dependencies, upfront investment, and specialized expertise. It’s important to carefully evaluate the different AI options available and choose a solution that aligns with your needs and resources.
- Do nothing
- Cons: In today’s fast-paced, competitive environment, doing nothing should not be considered an option. Technology is rapidly evolving, adoption is rising, and global economic pressures are intensifying. Failing to embrace new technologies and continuously improve processes can lead to declining competitiveness and profitability.
Concerns when evaluating operational improvement options
When evaluating the different options for improving production efficiency, factory operations teams need to consider several key factors:
- Capacity strain on resources: Implementing new solutions can strain already stretched resources. It’s important to choose solutions that minimize the burden on internal teams and provide quick time to value.
- Cost: High upfront costs can be a barrier to adopting new technologies. It’s essential to evaluate the total cost of ownership, including upfront costs, ongoing maintenance, and support expenses.
- Risk of failure: The risk of failure is a major concern when implementing new technologies. Choosing solutions that are low-risk, easy to implement, and proven to deliver results is crucial.
- Interruption of existing operations: Any new solution must be carefully integrated into existing operations to avoid disruptions. Non-intrusive, passive solutions are ideal for minimizing operational impact.
Visual AI – A new technology option that achieves what other options can’t
Visual AI is a new, effective solution for improving OEE and overall efficiency:
- Transform existing CCTV camera investments: Convert your existing CCTV cameras from reactive to proactive visual sensors, capturing full visual traceability of all the moments that matter.
- Leverage the best of human and AI: Allow AI to handle the heavy lifting of monitoring production operations 24/7, capturing and analysing business-critical metrics. Meanwhile, your Factory Operations team can access real-time insights in their pockets, enabling them to apply their unmatched expertise and take necessary actions.
- Real-time data: Provides immediate insights, allowing for quick responses to issues as they arise.
- Unbiased and objective: Eliminates the subjectivity and inconsistencies of manual data capture, providing accurate and reliable information.
- Low-risk: Uses existing infrastructure and integrates seamlessly with current operations, minimizing disruption and reducing costs.
About the Author
visionAI is at the AI Software-as-a-Service company with AI-driven solutions for manufacturing operations. Specialising in Visual AI, we help manufacturers transform their production efficiency through real-time data and proactive insights. Our AI models are designed to work seamlessly with existing infrastructure, providing low-risk, high-reward solutions that drive measurable improvements in OEE.