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  • 1.  Maintenance spare parts and utilities cost Forecasting

    Posted 10-11-2021 12:42 PM
    Hello colleagues,

    I'm working in food manufacturing plant as maintenance manager. I'm preparing now forecasting for 2022 spare parts and utilities forecasting. I'm using trends of last 2 years to forecast next year spend (utilities like Electricity, water and fuel consumptions) also for spare parts. what are your recommendations for techniques that could be used to forecast relevant spend?

    Thanks,
    Abdelrhman Ragab
    Maintenance Manager

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    Abdelrhman Ragab
    Americana
    Dubai
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  • 2.  RE: Maintenance spare parts and utilities cost Forecasting

    Posted 10-11-2021 01:33 PM
    Hello,

    Assuming your production rates are similar 2022 (otherwise adjust), utilities should be close enough for the past 2 years.  Maintenance spare parts can be a tad trickier since the maintenance cycle for equipment often is (hopefully) more than 2 years, so I would probably try to:

    1.  Establish a baseline budget by adding big ticket items in the budget (big rebuilds and projects for 2022.  Previous years probably won't help much since these may be things that are done seldom, or just once.  Also put in the medium expensive items you know about from backlog.

    2.  Add the consumables, but look at 5 years and see if you have any blips (expensive equipment/ repairs etc) that may come up again.  Make sure not to overlap with (1.) if possible,

    Hope this helps

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    Torbjorn Idhammar
    President & CEO
    IDCON, Inc.
    http://www.idcon.com
    Raleigh NC
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    Original Message


  • 3.  RE: Maintenance spare parts and utilities cost Forecasting

    Posted 10-12-2021 10:56 AM
    For spare parts, your next question should be how to access and join historical data from multiple systems (CMMS and materials management) into a super table that distinguishes subsets such as maintenance type, asset type, operating environment, etc.

    Describing how to tally totals by ticket size and consumables is largely meaningless if we can't ultimately work with our data to arrive at viable numbers.

    Richard G. Lamb, PE, CPA






    Original Message