Mold Maintenance & Repair

OCT 2014

Mold Maintenance & Repair

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October 2014 17 transmitter) that is installed on each molding press and wirelessly communicates with the third component, a "gateway" that is installed in each molding facility. The gateway connects via Ethernet to transmit a mold's data in real time to a secure, remote database. From there, customers can log into a website and view information for each mold they have connected to the system, and they can do it without any geographic limitations. What information is available? The moni- toring system can be confgured to provide real-time alerts when a mold is not operating within user-defned limits. For example, a user can set required preventive maintenance (PM) intervals and be notifed if a mold is approach- ing required PM or if the mold is overdue for PM. A notes section allows users to record what has been done to the mold during mainte- nance. Real-time performance measures, such as cycle time and effciency, are also tracked, and users are informed, in real time, if a mold is not performing within predefned limits. In this system, each mold is a node on a network. Each of these nodes has information that can be acquired from it. The data that is generated by it is used, in real time, to drive the decisions made by each of the mold's stakeholders. This is the application of Big Data concepts and the Internet of Things to molds. Big Data and Mold Maintenance One way injection molding companies can use the data provided by a mold monitoring system is to plan and schedule PM for molds, even at multiple manufacturing plants. This offers the shop real-time visibility of current and upcoming PM needs for its molds. This information then can also aid in the decision-making process. Here is an example of how one OEM ana- lyzed cycle-time trends for existing tools from reports generated by its monitoring system. from sensors located on each windmill are combined with real-time weather conditions and electrical needs information to determine when and how to run each windmill. Using this system has led to effciency gains of fve per- cent from existing wind farms. In this scenario, each windmill is a node on the network (the power grid) that generates data that is then used to drive decisions and optimize results. Other operations also are using the Internet of Things and Big Data to reduce labor costs while making better decisions. For example, when tool cribs are used to replenish cutting tools, someone does a "milk-run" and physical- ly counts the number of end mills, taps or drills that are usually stored in each drawer. New items are then ordered based on the tool crib attendant's opinion of what should be in inven- tory. At a minimum, systems like this are costly and highly subjective, and frequently lead to tooling shortages. In many shops today, however, cutting tools are dispensed from a vending machine. Just like the windmills in the previous example, the vending machine becomes a node on a network that automatically plac- es an order to ensure that the shop always has a suffcient amount of tooling available. These technologies have been applied towards countless industries; however, there has been limited impact within the world of production. Big Data Keeps Production on Target Mold manufacturers and molders can realize multiple advantages by employing these con- cepts within a mold monitoring system created specifcally for production tooling. Such a sys- tem consists of three components. The frst is a mold monitor—a small, low-cost, battery-pow- ered device that is installed on a plastic injection mold. It records each time the mold is cycled and calculates average cycle times and effciency measures for preceding weeks. The second component of the system is a press module (also known as a radio frequency One way injection molding companies can use the data provided by a mold monitoring system is to plan and schedule PM for molds, even at multiple manufacturing plants.

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