The first question that comes to mind is…what does it mean? Wikipedia says the word intelligence comes from the Latin verb intellegere, which means to understand. It further states that intelligence reflects a broader and deeper capability for comprehending our surroundings and applying knowledge in order to perform better in an environment.
这个定义后,主要目标nd benefit of the Manufacturing Intelligence solution is to provide a deeper understanding of the production process and environment, such that management and operations personnel can apply the knowledge to improve performance. For it to be most effective, the information has to be gleaned as close to real-time as possible, and must be made available to all who would benefit from it to make decisions.
In fact, if there were an equation for Manufacturing Intelligence, it might look like this:
Real-Time Data Collection and Management
+ Real-Time Data Analysis and Visualization
= Real-Time Decision Support
The result of applying this equation should be analysis of operational data that can be immediately acted upon to change and improve the performance of your process.
There are two important things to note about implementing Manufacturing Intelligence: 1) It is not something you can “buy” in a software product; 2) It is not a standard or a defined technology. Manufacturing Intelligence is more a strategy or way of defining and approaching solutions to problems and opportunities. However, a well-designed strategy will use software products that can make the adherence to standards and application of specific technologies easier.
The most important attribute of a good strategy is the ability to distill and filter raw plant information into role-based report and visual-aid formats that will facilitate the analysis of options to better utilize assets. Additionally, the strategy will often include the use of analytical technologies such as Overall Equipment Effectiveness (OEE), Statistical Process Control (SPC), Multi-Variate Analysis and Artificial Intelligence systems.
The one thing that must be common to every successful Manufacturing Intelligence strategy is commitment to the process and to the achievement of defined incremental success criteria metrics. In its 2009 survey “Manufacturing Performance Management,” Aberdeen Group Inc., Boston, identified a profile of the “Best In Class” top 20 percent of companies in their industries. The traits included being committed to formal processes and practices, commitment to continuous improvement and standards, and leveraging business systems and technology to achieve goals. Typical performance metrics included:
• 90 percent OEE
• 97 percent On-Time and Complete Shipments
• +6 percent Operating Margin vs. Corporate Plan.
实现这种程度的一个关键工具来支持performance is the Manufacturing Intelligence strategy. As with any project, a major key to a successful Manufacturing Intelligence strategy is the upfront definition of goals and planning. This is where an initial and ongoing Discovery Process is crucial to achieving true “Best In Class” continuous improvement. During this process, the appropriate stakeholders and intellectual resources come together, and as the name Discovery implies, build a “Best In Class” strategy.
Success keys
It is during the Discovery Process—defining and prioritizing the projects to implement the strategy—that the manufacturer can benefit from partnering with an independent systems integrator or solution provider. The partnership allows the manufacturer to take advantage of experience, proven methodologies and product-neutral consulting advice.
A Manufacturing Intelligence strategy built around a thorough initial Discovery Process may be just what you need to start making better informed, timelier decisions about your production operations.
Michael Bachelor, michaelb@bachelorcontrols.com, is a partner at Bachelor Controls, in Sabetha, Kan.
这个定义后,主要目标nd benefit of the Manufacturing Intelligence solution is to provide a deeper understanding of the production process and environment, such that management and operations personnel can apply the knowledge to improve performance. For it to be most effective, the information has to be gleaned as close to real-time as possible, and must be made available to all who would benefit from it to make decisions.
In fact, if there were an equation for Manufacturing Intelligence, it might look like this:
Real-Time Data Collection and Management
+ Real-Time Data Analysis and Visualization
= Real-Time Decision Support
The result of applying this equation should be analysis of operational data that can be immediately acted upon to change and improve the performance of your process.
There are two important things to note about implementing Manufacturing Intelligence: 1) It is not something you can “buy” in a software product; 2) It is not a standard or a defined technology. Manufacturing Intelligence is more a strategy or way of defining and approaching solutions to problems and opportunities. However, a well-designed strategy will use software products that can make the adherence to standards and application of specific technologies easier.
The most important attribute of a good strategy is the ability to distill and filter raw plant information into role-based report and visual-aid formats that will facilitate the analysis of options to better utilize assets. Additionally, the strategy will often include the use of analytical technologies such as Overall Equipment Effectiveness (OEE), Statistical Process Control (SPC), Multi-Variate Analysis and Artificial Intelligence systems.
The one thing that must be common to every successful Manufacturing Intelligence strategy is commitment to the process and to the achievement of defined incremental success criteria metrics. In its 2009 survey “Manufacturing Performance Management,” Aberdeen Group Inc., Boston, identified a profile of the “Best In Class” top 20 percent of companies in their industries. The traits included being committed to formal processes and practices, commitment to continuous improvement and standards, and leveraging business systems and technology to achieve goals. Typical performance metrics included:
• 90 percent OEE
• 97 percent On-Time and Complete Shipments
• +6 percent Operating Margin vs. Corporate Plan.
实现这种程度的一个关键工具来支持performance is the Manufacturing Intelligence strategy. As with any project, a major key to a successful Manufacturing Intelligence strategy is the upfront definition of goals and planning. This is where an initial and ongoing Discovery Process is crucial to achieving true “Best In Class” continuous improvement. During this process, the appropriate stakeholders and intellectual resources come together, and as the name Discovery implies, build a “Best In Class” strategy.
Success keys
It is during the Discovery Process—defining and prioritizing the projects to implement the strategy—that the manufacturer can benefit from partnering with an independent systems integrator or solution provider. The partnership allows the manufacturer to take advantage of experience, proven methodologies and product-neutral consulting advice.
A Manufacturing Intelligence strategy built around a thorough initial Discovery Process may be just what you need to start making better informed, timelier decisions about your production operations.
Michael Bachelor, michaelb@bachelorcontrols.com, is a partner at Bachelor Controls, in Sabetha, Kan.
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