Asset Management: Equipment Asset Management System Based on Siemens PLC Extends Equipment Life by Over 30%

Asset Management: Equipment Asset Management System Based on Siemens PLC Extends Equipment Life by Over 30%!

Hello, fellow engineers. I am Yang. Today, let’s discuss a very practical topic – using PLCs to create an equipment asset management system. This system can help companies save a significant amount of money. After implementing it in an injection molding factory, the equipment failure rate was directly reduced by 40%, and maintenance costs were saved by over 200,000 annually.

Why Implement Equipment Asset Management?

Equipment is like our body; it requires regular check-ups and maintenance. However, in factories, the approach is often “only treat when sick”; repairs are made only after equipment fails, similar to going to the hospital only after a serious illness, which delays production and incurs costs.

By establishing an asset management system through PLCs, it is akin to equipping the equipment with a “health monitor” that can timely detect issues and predict failures, transforming “reactive maintenance” into “proactive maintenance”.

System Architecture Design

Core Equipment:

• Siemens S7-1200 PLC (1214C DC/DC/DC)
• Analog Input Module (SM1231 4AI)
• Ethernet Communication Module
• Touch Screen (Jingzhi 7-inch)

Monitored Parameters:

1. Equipment Operating Time
2. Motor Current
3. Temperature
4. Vibration
5. Lubricating Oil Pressure
6. Production Count

Key Points in PLC Program Design

1. Operating Time Statistics

less copy

// Using a combination of counters and timers
TON_TIME(IN := "Equipment Running Signal",
         PT := T#1H,
         Q => "Hour Count Trigger",
         ET => "Real-time Operating Time");

CTU_hour(CU := "Hour Count Trigger",
         R := "Reset Signal",
         PV := 8760,  // Number of hours in a year
         Q => "Annual Maintenance Reminder",
         CV => "Cumulative Operating Hours");

1. Warning Judgement

abnf copy

// Multi-level warning example
IF "Motor Current" > "Rated Current" * 1.2 THEN
    "Minor Warning" := TRUE;
ELSIF "Motor Current" > "Rated Current" * 1.5 THEN
    "Major Warning" := TRUE;
    "Emergency Stop" := TRUE;
END_IF;

Data Collection and Processing

Key Point: Sampling Period Selection

• Fast-changing parameters (e.g., current): 100ms
• Medium-speed changing parameters (e.g., temperature): 1s
• Slow-changing parameters (e.g., operating time): 1min

Data processing uses moving average filtering to eliminate sudden disturbances:

clojure copy

// 10-point moving average
FOR i := 9 TO 0 BY -1 DO
    "Sampling Array"[i+1] := "Sampling Array"[i];
END_FOR;
"Sampling Array"[0] := "Current Value";

"Average Value" := 0;
FOR i := 0 TO 9 DO
    "Average Value" := "Average Value" + "Sampling Array"[i];
END_FOR;
"Average Value" := "Average Value" / 10;

Predictive Maintenance Strategy

Establish equipment health models based on historical data:

1. Normal Range: Equipment parameters within 10% of rated values
2. Attention Range: Exceeding rated values by 20%
3. Warning Range: Exceeding rated values by 30%
4. Alarm Range: Exceeding rated values by 50%

Maintenance Reminder Logic:

• Operating time reaches 80% of maintenance cycle: Schedule maintenance in advance
• Parameters enter attention range: Increase inspection frequency
• Parameters enter warning range: Prepare spare parts
• Parameters enter alarm range: Immediate shutdown for repair

Communication and Data Storage

Use Ethernet to upload data to the database:

clojure copy

// TCP communication program segment
"TCON_DB"(REQ := "Send Trigger",
          ID := W#16#1,
          CONNECT := "Connection Parameters",
          DONE => "Connection Completed",
          ERROR => "Connection Error",
          STATUS => "Status Code");

"TSEND_DB"(REQ := "Send Allowed",
           ID := W#16#1,
           LEN := "Data Length",
           DATA := "Send Buffer",
           DONE => "Send Completed",
           ERROR => "Send Error",
           STATUS => "Send Status");

Actual Application Effects

Implementation data from an injection molding factory:

• Equipment failure rate: Reduced from 3.2 times/month to 1.9 times/month
• Unplanned downtime: Reduced by 65%
• Maintenance costs: Reduced by 235,000 annually
• Equipment life: Expected to extend by 35%

Precautions

1. Strict Sensor Selection:

• Temperature Sensor: Preferably PT100
• Current Transformer: Use Hall effect type
• Vibration Sensor: Use acceleration type

1. Grounding and Anti-Interference:

• Sensor signal lines must be shielded
• PLC should have independent grounding
• Field signals should be well isolated

1. Data Backup:

• PLC program dual backup
• Parameter records exported regularly
• Historical data backed up off-site

Practical Suggestions

1. Start with a single machine pilot, then expand after maturity
2. Prepare an equipment list:

• Name and specifications
• Installation date
• Maintenance records
• Spare parts information

1. Establish standard documentation:

• Operation manual
• Maintenance procedures
• Emergency plans

1. Train maintenance personnel:

• System principles
• Fault diagnosis
• Data analysis

1. Establish evaluation mechanisms:

• Monthly analysis meetings
• Quarterly evaluation reports
• Annual optimization plans

Equipment asset management is a systematic project that requires the integration of technology and management. The above is the implementation plan based on Siemens PLC. With this system and diligent execution of the maintenance plan, extending equipment life by over 30% is entirely feasible.

THE END

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