From the plant floor
Three stories from a bakery.
Before the home lab there was a plant: a US bakery in New York, where I was plant manager. Cakes, brownies and mini desserts, baked, frozen, cut, packed and shipped on pallets. These are three of the improvements I am proudest of, told short. The numbers in the calculator are illustrative; the structure and the stories are real.
Story 1 · capacity
Take the traffic out of the factory
Every order was promised with one number: a ten-day lead time. Nobody could say what an order really needed, so the floor was full of traffic: trolleys everywhere and drums of batter waiting.
I started from the order and worked backwards, area by area, each in its own unit. One box of IWP brownies is 96 pieces. One piece is about one ounce, so one tray is 96 ounces, plus 5 % for production loss. Trays become batter, batter becomes whole drums of 600 or 300 lb, drums become mixer batches, trays become oven batches and trolleys, and every area gets its hours and its people. Suddenly we could see what each area really needed, and where the real constraint was.
Before
- About 90 trolleys parked in front of the brownie cutter, which can cut at most 75 trays a day.
- Filling lines filled what they wanted; mixing produced ahead, so batter aged in the drums.
- Trolleys were blocked for every other area; product waited, and some of it expired.
After
- Trolleys in rotation capped at what the bottleneck needs: the rest went back to work for the other areas.
- Pull at filling: the filling line is the pacemaker and sends mixing one signal per drum.
- Ship dates from capacity, not from a fixed ten days.
Lesson: more WIP in front of a bottleneck does not make it faster. It only hides the constraint and steals resources from everybody else.
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Story 2 · FIFO
A FIFO lane for cooling trolleys
After baking, product cools on its trolley before confectionery. It needs at least 30 minutes, and after 24 hours it is no longer good. Without a rule, trolleys were parked wherever there was space. Some were found too late; some were simply lost, and the product was scrapped.
Before
- No order in the cooling area; the newest trolley was often the easiest to reach.
- Lost trolleys and scrapped product: pure cost of poor quality.
After
- A marked first-in, first-out lane, run as a workshop with the team: in at one end, out at the other.
- A visible window of 30 minutes to 24 hours on every trolley.
- No more lost trolleys and no more scrap from expired cooling.
Lesson: FIFO is the cheapest quality system there is. It needs paint, a rule and a team that owns it.
Story 3 · 5S
5S in a −28 °C freezer warehouse
Finished product waits on pallets in the freezer warehouse until it ships. Nobody wants to spend more time than necessary at −28 °C, and it showed.
Before
- Half pallets and lost pallets.
- R&D and quality retention samples without labels.
- Semi-pallets with no ID, no owner and no best-before date.
After
- 5S, and pallet positions grew from 200 to 300 in the same room.
- Workflows for R&D and quality retention samples, ready for any audit.
- A coloured foil for each of the top five customers, and a coloured sticker for each palletizing day.
- Weekly random audits: a sticker colour that does not match the day means a pallet is a week old. It gets a second sticker and the customer is contacted. From then on, the ten-day lead time issue was no longer the plant's fault.
The result: less time searching, faster loading, a higher service level, and a project that was recognised and applauded at group level.
Lesson: visual management works best where people least want to stand and think. A colour you can see from the door beats a list on a clipboard.
Want this for your plant?
Zenilify Consulting brings the same approach to food and manufacturing plants: capacity from the order backwards, FIFO and pull where they pay, and 5S that survives the audit.
Book a diagnostic callOpen the capacity calculator
