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Dairy Factory Pasteurization Line Engineer

Freelancer

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placeAU home_workリモート assignment契約社員 public集約求人 · AU

event2026年9月02日に公開 · verified2026年9月02日時点で募集中であることを確認済みです

AU$ 30 – AU$ 250 /案件

求人について

I need an Engineer in Food/Industry/Agricultural It is a project work The Story: Pasteurization Line Problem Setting: A mid-sized dairy factory runs a plate heat exchanger (PHE) to pasteurize milk using the HTST method (High Temperature Short Time — typically 72°C for 15 seconds). 1. Observed During peak production hours, operators notice the outlet milk temperature from the heat exchanger occasionally dips below the required 72°C setpoint. The automatic diversion valve keeps kicking in, sending under-processed milk back for reprocessing — wasting time and energy. 2. Analysed The engineer investigates: -Measure the flow rate -Calculated the required heat capacity -Determined the performance of plate heat capacity -Evaluated the relationship between flow rate, temperature difference, Pressure drop -Check the residence time After the investigation, Analysed → Calculated → Compared → Decided → Implemented → Verified 3. Calculated Turn the raw data into numbers you can act on: Required heat duty: Q = ṁ·Cp·(T_out − T_in) using current flow and target temperature. Actual/available heat duty: based on the PHE's heat transfer coefficient (U), surface area (A), and the log-mean temperature difference (LMTD) between hot and cold streams — Q = U·A·ΔT_lm. Residence time: Volume ÷ flow rate, checked against the 15-second HTST minimum. Pressure drop trend: how ΔP changes with flow rate and with time since last cleaning (fouling indicator). This tells you where the shortfall is — e.g. "at 1500 L/h, required duty exceeds available duty by X kW" or "residence time drops below 15 sec above 1400 L/h." 4. Compared Lay out multiple operating scenarios side by side (like the table from before) — different flow rates, pressure drops, and resulting pasteurization temperatures — and compare each against: The regulatory/food-safety requirement (72°C for 15 sec, or your local dairy code equivalent) Energy cost implications of each option Throughput/production implications of each option 5. Decided Pick one course of action, with justified reasoning — not just "reduce flow rate" but why that option, over the alternatives, given the trade-offs found in the comparison. Common decision paths: Reduce/cap flow rate during peak hours Increase CIP (cleaning) frequency to control fouling Adjust hot-water/steam supply temperature or flow to increase available heat duty Some combination of the above 6. Implemented Describe the actual change made: new setpoint, new cleaning schedule, updated SCADA alarm thresholds, staff briefing, etc. 7. Verified Monitor the same parameters (outlet temp, pressure drop, diversion valve activations) over a follow-up period (days/weeks) to confirm the fix worked, and document the before/after comparison.

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