Your Laboratory: Four steps at three stations 1)Sample Preparing –Step 1 blood is transferred to test tubes in the test kit 2)Testing –Steps 2 & 4 samples are tested and information is recorded 3)Centrifuging –Step 3 plasma and blood cells are isolated
Capacity Costs Station #1 SAMPLE PREPARING MACHINES – $90,000 each Station #2 TESTING MACHINES – $80,000 each Station #3 CENTRIFUGING MACHINES – $100,000 each Resale value for any machine – $10,000 each
Factory Process Every step has its own process time Littlefield measures average daily utilization rates at each station Queues hold waiting jobs The Lab holds a maximum WIP of 100 orders lead time = process time + wait time
Orders and Kits Every arriving customer order is matched with a new test kit – test kits cost $600 each – shipments have a fixed ordering cost = $1,000 – suppliers lead time is always 4 days Three criteria to place an order: 1)Inventory on-hand is lower than the reorder point 2)There are no shipments of materials in transit 3)Cash on hand is sufficient for the order quantity
Reorder Point – Stocks are replenished when they reach some pre-determined low point. A system commonly used by squirrels Well, also by you, your checkbook vendor, and many other systems. – You start with 160 kits in stock – Your reorder point ROP is set at 40 kits – The order quantity Q is set at 120 – You can change both ROP and Q – See your inventory chapter for helpful ideas.
Contract Pricing < 24 hours = $1000 > 72 hours = zero *Factory must still purchase inventory for orders earning zero revenue ! Contract Pricing Three contracts to choose from 1)quoted lead time = 7 days, max lead time = 14 days, price = $750 2)quoted lead time = 1 day, max lead time = 3 days, price = $1000 (pictured here) 3)quoted lead time = 12 hours, max lead time = 24 hours, price = $1250 An example using Contract 2 24 hours = $1000 72 hours = zero * Factory must still purchase inventory for orders earning zero revenue !
Logging Into Your Laboratory after the simulator has been initialized Today http://lab.responsive.net/lt/pdx/entry.html
example Enter team name Logging Into Your Laboratory
Enter teams password example Logging Into Your Laboratory
Click Plot Job Arrivals and Download Data Click download button Save to desktop Open with MS Excel or another spreadsheet application Copy > Paste data columns to a master worksheet Index by Day
Opening the data in Excel You will have 50 days worth of data until it starts running dynamically on Feb. 3 The demand will increase until around day 150 and then level off Figure out the demand point where it levels off day number of jobs arriving each day 12 22 31 40 52 61 70 82 92 103 111 …… 486 499 506
Forecasting Demand (arrival rate of jobs) Overall Linear trend = SLOPE(known_y's,known_x's) = INTERCEPT(known_y's,known_x's) Forecast for the demand at the point where you think it will level out.
Look at Capacity Problems (station 1 Queue Box)
Click on Station 1 to see Utilization Might want to see what happened
Click on Materials Buffer Box to see your inventory policy & status As demand goes up, What could happen here? What can you do?
Current Job Lead Time through system & contract information
Expected Utilization = Key Hints Forecasts estimate future outcomes They are not known for precision A prediction interval should be considered Arrival Rate * Process Time # of Machines
Key Hints Balance your work stations, reduce bottleneck Proactive are better than reactive strategies Monitor your inventory and change ROP and Quantity if you need to. It takes 4 days for part orders to arrive from your supplier so make sure not to run out during lead time. Watch your completed job lead time/revenue to take most profitable contract when possible
Deliverable No more than 2 written pages (then appendices) which cover your teams experience What did you do (in sequence)? Why did you make that decision? How did it work out? What did you learn during the process? Include an Appendix with a journal and any relevant calculations.