The 4 components of reliable systems in stamping

Yasin ATEŞ

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Yönetici
Vip Üye
10 Haz 2020
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Stamping companies often use production-generated data to make better decisions during their design, build, operations, and maintenance activities, but that data must be reliable and accurate. Monitors and data exposed to possible manipulation, excessive noise, dirt, and poor calibration will generate unreliable and inaccurate data. And bad data leads to bad decisions.

System Components​

Every reliable system comprises four components. From an advanced IoT network to an operator making a basic operational decision, your system components include data and transactions. The usefulness of the system depends on the integrity and accuracy of the data and transaction execution.

Data is the observed or human-entered information and attributes collected, acted upon, and stored. Designing data includes determining what data to collect and store and defining how data components are related. Data normalization is used to design efficient databases and eliminate redundancy and ambiguity.

Transactions are the basic activities that add, change, delete, or look up a data record based on some input stimulus. The input may include human entry from a device, a status change on a monitored component, or a call from an application interface.

Integrity ensures that information is used consistently and managed reliably to support decision-making. This means transaction initiators are from authorized agents only; transaction failures are rolled back across all cascading transactions to their initial state; redundant or standby tools are available to handle transactions in case of transaction, application, network, or hardware failure; and process failures are captured and alerts sent to the user.

Accuracy is a critical component of integrity, but it must be considered separately because the risks associated with inaccurate information can be hidden from view and harmful to your operations. Transactions must be tested for accurate results. Continuing procedures also must be employed to ensure the accuracy of monitoring data. The results of inaccurate data include poor decisions and missed problems. The consequences can include forming failures, early equipment failure, and unsafe working environments.

Components in Tonnage Monitoring​

As an example, let’s take a look at tonnage monitoring on a press. The tonnage monitor creates a signature of the force generated throughout each stroke of the punch. Understanding your tonnage signature allows you to set your dies with fewer adjustments, manage your press to minimize wear and tear on both the press and die, and prevent hard hits. Maintenance personnel can use the information to monitor load balancing and component wear.

Tonnage monitoring uses a strain gauge to measure deflection under load, whether tension or compression. The sensor converts the energy from strain to an electrical charge which can be translated to tonnage or press load.

The tonnage signature is an important measure of the efficiency of your press operation. Accurate measures can highlight issues involving lubrication, hardness, thickness, tool wear, misfeeds, and scrap or contaminants in the die.

Given this brief summary, the system components and their controls might include some of the following:

  • Data collected—Press ID, cycles since last repair, blank lift identification, tonnage signature, die identification, lubricant.
  • Transaction generated—Press operational status, error event, press unbalanced warning.
  • Integrity—Access to data is controlled; data failures are captured and rolled back; processors are redundant; processors are maintained in a clean location; press noise is managed to prevent signal degradation.
  • Accuracy—Strain measures are calibrated at an appropriate frequency; strain gauge attachment points are firm; strain gauge placement is appropriate.
Accurate and reliable information about your press tonnage curve will help your employees to make more informed decisions, resulting in better die design, less wear on the die and components, timely maintenance actions, less downtime, less scrap, and consistent-quality formed components.

Beyond the Technology​

As we rely more on statistical analysis of operational data, the accuracy of all our generated data becomes critically important to decision-making. If the accuracy of generated data begins to drift, so will the analysis generated from that data. Inaccurate analysis can lead to less-than-optimal decisions and even catastrophic failure.

Available monitoring devices and evolving technologies offer manufacturers a tremendous opportunity to learn from their operational information. But monitoring and analysis implementation must go beyond the technology and include procedures to ensure that monitors are calibrated, noise is eliminated from the system, and unauthorized manipulation is prevented. Any decision-support project must include a failure mode and effects analysis to identify the greatest risks and procedures to ensure the accuracy and integrity of your information.

We don’t need to look far for an example. Social media does a tremendous job of collecting and sharing information, but it fails us because there is no effort to ensure the accuracy and integrity of that information. Social media is proving to be a destructive force because bad actors propagate deceptive and deceitful information. This bad information hurts people in their personal, professional, and political lives. The casual user has few alternatives to discern fact from fiction. This sort of destructive approach to technology development doesn’t belong on your plan floors.
 
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