AccomplishmentsMaterials Department

Pentair – WaterReynosa, Mexico

February 2006 to April 2007

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Initially, the situation was so desperate that improvements were implemented in phases; introducing “Quick Fixes” in each area allowed time for more permanent solutions to be developed.

Phased Improvements

Inventory Control Before

Pull systems in use at the plant were triggering production of the wrong parts

No connection between what was being produced and what was needed

After Introduced reference locations so that

we could find things Reorganized racks and put parts

needed by each Assembly Line next to each of the lines

Cycle Counting Before

Counting 30-40 parts per week, but only making adjustments on 3-4 parts per week

Fear of the financial impact of adjustments was the cause of the disconnect

No tracking of parts counted Known problems were not being

fixed Before production was started, all

parts were counted to make sure they were really there. (essentially 0% accurate).

After New philosophy

“Make adjustments fast” “Make big adjustments faster”

Location accuracy monitoring Root Cause investigations Focus on fixing process Focus on training Confidence in the system 98.8% net accuracy, 96.6% absolute

We changed the rules and turned a blind-eye to the financial impact, focusing instead, on same-day correction of inventory discrepancies, fixing the causes of inventory problems, and regaining confidence in the system. Ignoring the financial impact of adjustments initially caused great concern, but as the inventory adjustments stabilized the fear proved to be groundless.

Accuracy Tracking

The net adjustments during this time period (2006) were all positive. There had been a large inventory correction during a physical inventory in August as we re-set all the inventory levels. For months afterward we were in constant communication with the Engineering group in California fixing incorrect labels on boxes of component parts. An October 2007 physical inventory resulted in a 99.12% net adjustment (91.3% absolute).

Location Accuracy Control

The table above shows data collected early in the implementation of location counts (2006). During the following months, the table turned to nearly all green.

Emphasis on Training

My rule was that, if need be, we’ll repeat the training with any individual up to 3 times before finding them a new position. It was fairly typical that we needed to repeat the training at least once with each worker – often twice. It was rare that someone failed to get the message after the second or third retraining that we were serious about making change.

Production Control Before

3 skids per week of duplicated production

The same sales order was often made twice

After April 2006: Introduced a combination

work order/sales order document Since the document was printed only

once, we eliminated the duplicate production problem

One week’s worth ofduplicated production

Creation and implementation of an Access database to control production. January 2008 note: This program is still be used and has operated continuous since my departure without maintenance to the program.

The highlights indicated that the production was complete. All that was necessary to duplicate the production was one of the shift supervisors failing to make the highlight. Less obvious was the problems associated with partial production of an order.

[Message from Sandra, January 2008]Hi Tim! =)Yes, your database still is in use. *~Thanks~*

Pull Systems Before

Pull system not maintained Cardboard wasted

After Reorganized pull system using

cards as signals Purchased Reusable bins 2 sigma 95% service level

philosophy

Boxes were discarded after one use

The philosophy in place on my arrival was a “Lean Application” based on dedicating molding machines to assembly work centers. This idea has worked in other locations, but in Reynosa this resulted in poor machine utilization. The introduction of 5 new molding machines was thought to be an absolute requirement. When I changed the mindset to shared utilization of molding machines, we found that this $1.6 million of proposed capital spending was unnecessary.

Queue – Load Analysis

Created visibility into the amount of work at the plant. Prior to this, there was no way to see and understand trends in order to make decisions about staffing levels in Operations.

Rough Cut Capacity Overview Molding Center RCCP

Created the ability to see load vs. capacity Created the ability to “Build Ahead” molded parts to

avoid deterioration in past due during the busy season

Created the ability to see demands on particular molds

The chart shown above could be updated at the push of a button. By referencing the information above we were able to redirect molds to machines and better balance the machine utilization. Having real time data allowed us to continually evaluate mold and machine load and make adjustments to match our capabilities to projected sales.

Created dispatch lists giving Production Supervisors and Planners detailed information about queue levels in front of molding and assembly work centers. Prior to this, there was no way to see the load in front of each machine, no way to prioritize work, no way to provide feedback on completion dates to Customer Service.

•A non-blank entry here indicates that an order is late to the Spa/Bath Customer•This information is tied to the “Spa/Bath” Late-to-Customer Data

•The new direction to the planners is to stop printing travelers if the material is not available.•“Molding” in this field indicates that components still need to be molded•We plan to introduce a new code “At Machine” which will indicate that the part is soon to be completed. In this case, it will be ok to give the traveler to Assembly

•Note that there are generally 2 persons working in each Assembly Cell

•Traveler has been printed and is at the Assembly Cell

•The Planner should start to select orders to print based on material availability and urgency instead of blind adherence to the due dates•We will modify our practice of blindly printing all travelers of a particular part to be run back-to-back

•We need to start watching work centers and correcting routings when they are incorrect.

Dispatch List Creation

Created Rough-Cut capacity reports which could be automatically updated, creating visibility to what was happening at each work center both current and in the coming 4 months.

Pool Items cross-referenced to Reynosa work

centers

Rough Cut Capacity information by Cell.

Updated daily

All demands integrated

Rough-Cut Capacity Planning Detail

Purchasing Before

MRP driving false demands No clear ordering processes No way to analyze demands for

purchased parts No way to tell who buys the part $150,000 of Excess inventory added

monthly $4.0 million dollars of open POs! E-mail ordering of parts Panic buying

After Implementation of buyer codes Implementation of web-based kanban

system Designation between high volume parts

replenished by pull and low volume purchased using MRP

$180,000 of open POs Eliminated blanket purchase orders Plan for Every Part

E-kanban System

The web-based tool shown had been implemented by the IT group at the headquarters in North Carolina, but none of the sites within the Division were making full use of it’s functionality. I invited the IT group to come to the plant and help us install this tool. The results were nothing short of amazing.See the following inventory reduction on the next slide.

Inventory Turns & Inventory LevelsInventory Turns - Reynosa

COGS/[(BI+EI)/2]

3.113.51

1.991.57

2.362.56

3.102.74

3.102.82

4.31 4.46

$8,580,586

$7,729,356

$6,972,000$6,616,134

$6,434,136$6,087,067

$5,754,472$5,958,990$5,815,694

$7,431,911

$8,714,958$8,399,112

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$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

$6,000,000

$7,000,000

$8,000,000

$9,000,000

$10,000,000

Inve

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Turns Inventory COGS std orders COGS DRKP:\Sandra Data\Inventory Turn Calculations\Turn Calculations

The introduction of the web-based Kanban system and the elimination of blanket orders and uncontrolled e-mail ordering had an immediate and sustained impact on inventory levels. Inventory levels at the plant dropped by $3 million. The decrease was sustainable even as sales volume increased.

Materials’ Department Before

Buyers were operating without supervision.

Planning was not performed.

After Planners control production schedule Communication of expected ship dates

to Customer Service Excel Training Data collection and analysis by staff

members Very strong planners & buyers

Once a department was formed, synergies emerged between Production, Purchasing and Planning processes

Value Stream Mapping – Distribution

Distribution Assembly

Partnering with the PIMS group and division’s Distribution Centers, we created Value Stream Maps to target our efforts both within the plant and within the overall supply chain.

Inter-site ERP Problems Before

Forecasted demands were being doubled and tripled

Inventory rose by $3 million from bad MRP data

Forecasts did not “net-out” inventory at the distribution centers

After Reorganized demand flow to transfer

demand from the DCs to the Plant, netting out inventory at the DCs

In researching the Supply Chain Process, I discovered that forecasts were being loaded directly onto the plant, driving component inventory even when sufficient quantities of finished goods were sitting at the DCs. QAD already had tools for correctly routing demand through distribution centers but it wasn’t until we team-up with IT that we were able to correctly diagnose the error and reorganize the demand flow.

Data! Before

No item master Leadtimes not loaded Safety stocks and order

parameters in chaos We didn’t know who the

suppliers were

After Routings overhauled Work Centers Reorganized Item Master exists We know which items need to be

stocked Supplier codes added

I will never forget asking to get the item master for the Spa Bath Division and being told that such a thing did not exist.

Cycle Times – time between receipt of order and ship date SDC: Stocked at the DC’s ATO: Assembled when we receive a customer order CSO: Customer Special Order

Customer Service levels increased and cycle times decreased at the same time that inventory levels fell both at the plant and at the distribution centers.

The Materials Team Reynosa 2006

Andre Fleury, Plant Manager; Sandra Esparza, Planner; Claudia Garza, Buyer; Ricardo Gongora, Planner; Tim Bina, Materials Manager; Enrique Villarreal, Shipping Receiving Supervisor; Elizabeth Varela, Inventory Control Supervisor.Jan 2008 note: Except for Elizabeth (who found a job outside Pentair as a Materials Manager) and myself, this team is still in-tact in Reynosa despite high turnover levels in the city. The skill level among this group of employees is as strong as anywhere in Pentair. Jeff Henson, who I interviewed and recommended as my replacement, is now the Materials Manager and is continuing to lead improvement efforts in both Reynosa and North Carolina.