analysis of gap inc - mie. - university of toronto · pdf fileanalysis of gap inc. brampton...

Analysis of Gap Inc. Brampton Distribution Centre Inbound Operations

Annette Selvanayagam

A thesis is submitted in partial fulfillment of the requirements for the degree of

BACHELOR OF APPLIED SCIENCE

Supervisor: Professor D. Frances

Department of Mechanical and Industrial Engineering University of Toronto

March 22nd. 2007

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Abstract The following thesis applies a combination of problem solving techniques such as simulation modeling, Business Process Reengineering (BPR) techniques and line balancing concepts to improve Inbound operations within Gap Inc. Brampton Distribution Centre. Prior to the thesis, the Inbound team was unable to meet its shipment stocking deadlines and experienced a drop in Team Receiving productivity which accounted for 80% of the labour hours. By utilizing simulation modeling and other BPR techniques, inefficiencies related to the Team Receiving process and the management of the shipment stocking deadline were identified. This document concludes with new strategies/processes to improve workload management and to ensure processes are aligned with business needs.

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Acknowledgements

I would like to thank Professor Daniel Frances for his support and guidance over the course of this thesis project. In addition, I would like to extend my gratitude to the Inbound Team at Gap Inc. Brampton Distribution Centre. Their information and assistance played a significant role in this project.

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i. Table of Contents

1.0 Introduction……………………………………………………………………….... 1.1 Purpose Statement………………………………………………………... 1.2 Company Background…………………………………………………….. 1.3 Motivation………………………………………………………………...… 1.4 Project Focus……………………………………………………………….

2.0 Literature Review………………………………………………………………….. 2.1 Business Process Reengineering……………………………………….. 2.2 Simulation………………………………………………………………….. 2.3 Line Balancing……………………………………………………………...

3.0 Methodology Overview……………………………………………………………. 4.0 Process Description Development ……………………………………………....

4.1 Development of Team Receiving ‘As-Is’ Model……….……………….. 4.1.1 Description of Current Team Receiving Process……………… 4.1.2 Description of Team Receiving ‘As-Is’ Model…………………..

4.2 Description of ‘On Time to Stock’ Metric Management Process……... 5.0 Problem Analysis………………………………………………………………….. 6.0 Process Redesign Development…………………………………………………

6.1 Redesigning Team Receiving Process…………………………………. 6.1.1 Simulation Testing Objectives and Procedures………………... 6.1.2 Results and Recommendation…………………………………...

6.2 Redesigning ‘On Time to Stock’ Metric Management process ………. 7.0 Conclusion…………………………………………………………………………. 8.0 References…………………………………………………………………………. 9.0 Appendices……………………………………………………………………...…. 10.0 Figures…………………………………………………………………………….. 11.0 Tables……………………………………………………………………………...

1 1 1 2 3 5 5 6 8 9 11 11 11 14 16 17 19 19 19 20 22 24 25 26 29 36

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List of Figures Figure 1: Team Receiving Process Map Figure 2: Team Receiving Simulation Model Figure 3: Probability Distribution of POs per Trailer Figure 4: Probability Distribution of SKUs per PO Figure 5: Sample Inbound Team Sheet Figure 6: Probability Distribution of Cartons per SKU Figure 7: Probability Breakdown of SRAT station sub-processes Figure 8: Current Team Receiving Productivity Figure 9: Three Man Team Test Results

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List of Tables Table 1: Simulation Software Packages Table 2: Expected Cycle time of Team Receiving Workstations Table 3: Sample MOST Expectation Documentation Table 4: Sample Team Receiving Business Objects Report Table 5: Sample Labour Management System Report Table 6: ‘As-Is’ Simulation Model Results Table 7: Sample Three Man Team Simulation Test Results Table 8: Sample Inbound Trailer Log

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1.0 Introduction 1.1 Purpose Statement The purpose of this thesis project is to improve Gap Inc. Brampton Distribution

Center‟s (BDC) ability to meet its key performance metrics for its Inbound

operations. In order to achieve this objective, a combination of problem solving

techniques including simulation modeling will be applied.

1.2 Company Background

Gap Inc. is a specialty retail network consisting of four recognized apparel brands-

Gap, Banana Republic, Old Navy and Forth & Towne. It owns all aspects of its

supply chain business (i.e. Stores, Distribution Centers) aside from Manufacturing

and Transportation. Within Canada, currently there is only one Distribution Centre

(DC) – BDC that processes orders for stores across Canada.

As a part of the Logistics Sector, BDC management primarily aims to meet

performance metrics (i.e. productivity rates, cycle times, turnover rates, frequency of

accidents) set by the Gap‟s Logistics management while minimizing costs related to

labor and overhead. BDC must comply with performance metrics to receive

products within a specific deadline even if it requires overtime hours and the

products will remain stocked within the facility for over a month. In addition, store

needs are given higher priority over costs incurred by the DC to comply with the

needs. For example, if a store wants only one unit of multiple SKUs to replenish their

stocks, BDC must complete this order by unit picking the order even though it is

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more labor efficient for BDC to case-pick orders. Thus, operations are largely

dictated by requirements set by the Logistics management.

Within BDC operations, all job functions are either categorized under Inbound or

Outbound processes. The scope of this thesis will only cover Inbound Team

operations, which include Team Receiving, Multifunction, Vendor Audit, and Load

Put away of Pallets (Job functions will be explained in detail under Process

Description Development).

1.3 Motivation & Expectations

During my Professional Experience Year within Gap Inc., there were two DCs that

stored and processed orders for stores across Canada. Near the end of my term,

the two DCs were consolidated into one DC. Following this major change, the

Inbound team experienced challenges in meeting their key performance metrics. As

a result, I was presented with this problem as a thesis project.

One of the main changes in Inbound was the change in management. Some of the

new supervisors had limited experience in Inbound operations. Therefore, BDC

management team became interested in streamlining their operations by identifying

better ways to manage their employees and solutions to overcome current

bottlenecks in their Inbound processes.

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1.4 Project Focus

As mentioned in section 1.1, the primary objective of this thesis is to improve BDC

Inbound team‟s ability to meet key performance metrics. Following discussions with

the Inbound manager and the supervisors, it was understood that the primary

requirements for this project was to overcome the following set of challenges:

Poor productivity within Team Receiving job function, which accounts for 80%

of labor hours in Inbound. Following consolidation, Team Receiving

productivity rate for the first two months was 57 Cartons per Direct Hour

(CPDH), which was more than a 20% drop from last year‟s performance of 69

CPDH. As the new Inbound management team and employees became

more accustomed to their responsibilities, productivity significantly improved.

However, they were still unable to meet or exceed last year‟s performance

level. Since this job function accounts for such a large portion of the labor

hours, all other job functions (i.e. Vendor Audit, Multifunction and Load

Putaway) were considered to be outside the scope of this project due to

limited time constraints.

Inability to meet performance „On Time to Stock‟ (OTS) metric. This metric

requires 90% of the shipments to be processed through Team Receiving

before their stocking deadline. The stocking deadline for each shipment is

usually three days following its arrival or two days following its arrival if it is an

airfreight trailer. Unfortunately, the Inbound management team missed the

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deadline for 30% of the shipments following consolidation. This is a significant

drop from last year‟s performance when only 5% of the shipments missed the

OTS metric requirements.

Following discussions with the Engineering Department Manager, it was also

understood that the project would focus on how simulation modeling could be

applied in other areas of the DC or Logistics and to identify the software most

appropriate to handle related complexities.

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2.0 Literature Review

Given the problem and challenges faced by the Inbound team stated in section 1.4,

this section provides existing research and applications related to various problem

solving techniques.

2.1 Business Process Reengineering

In an article written by Bush [1] regarding productivity improvement through

Business Process Reengineering (BPR), he explains that various changes such

innovative technology and unique customer demands are increasing the need to

challenge existing processes in order to achieve dramatic positive results. In order

to execute with this vision, the author also provides a series of guidelines to follow.

First, it is important to build direction by identifying business/team objectives and

critical success factors from a management perspective. Given the understanding of

project goals, the next step requires narrowing the scope by building an „As-Is‟

Model and conducting interviews/research in order to identify „quick hits‟ or

bottlenecks that require further analysis and evaluation. Following these steps, the

author suggests to begin redesigning the process by taking a clean-slate approach

and challenging any process constraints that do not align with the business direction.

The same approach must be applied when forming linkages between the

organization and its external counterparts. This step aims to ensure that proper

resources (i.e. people, policies, etc.) are available to support new processes. Finally,

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implementation steps occur during various stages of the BPR, starting with the

implementation of quick hits proceeding to training for the new processes.

2.2 Simulation

According to Simulation Modeling with Simul8 [2], the authors of the book describe

simulation as “the use of a computer program to model a real world system” that

enables the user to try different ways of operating the system. The Simul8 software

and other similar simulation software packages takes into account many important

factors such as productivity rates, probability distributions, travel distance, rate of

traveling, conveyor speeds, etc. Thus, this tool will play an important role within the

BPR approach.

As stated in 2.1, building an „As-Is‟ model of business processes will help identify

current bottlenecks and narrow the scope of processes that require redesign. In

addition, it will validate the new processes created during the design stage without

experimenting within the real system. However, simulation modeling does not

provide optimal solutions easily. According to Kempfer [3], optimizing operational

and business rules require running multiple tests and comparing outputs. This can

be a highly inefficient process.

In terms of simulation software options, there are various available for Distribution

Centre facilities/ Logistics related issues. According to Gaming Reality [4] - a

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simulation survey conducted by James Swain and other simulation articles, the

software packages detailed in Table 1 are utilized within the industry.

Table 1: Simulation Software Packages

Software Name

Applications Price Industry Usage

Arena Routing/dispatching strategy

Facility Design/Configuration scheduling

Workflow improvements

Decision support tool for capital improvements

$795 High

AutoMod Decision support tool for statistical and graphical analysis of material handling equipment in logistics

$2000 High

Extend Suite

High volume production line modeling

Building supply chain network [5]

$4000 Low

Flexism Managing Flexible Manufacturing Systems [6]

$12,500- $19,500 Low

ShowFlow 2 Facility Layout Design



$1500 Low

Simul8 Facility Layout Design



$5,000 High

Though all these software packages are fairly similar in terms of graphical model

construction, distribution fitting, output presentation, animation and real time viewing,

Arena is the most affordable software. In fact, it seems as though it is also the most

widely mentioned simulation software in many of the industry journals for

DC/Logistic related problems. For example, it was detailed in the following articles:

Simulation application for logistics strategy planning in the Baltic IT market

[7]: Arena is used to build a simulation model of the IT distribution system to

determine its logistic strategy planning

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Warehouse simulation creates a new model for change [8]: Simulation

software such as Arena allows companies to try different ways of designing or

redesigning the warehouse layout prior to installation.

Integrating simulation modeling and equipment condition diagnostics for

predictive maintenance strategies-a case study [9]: By utilizing Arena, a

simulation model was built to test various predictive maintenance strategies in

order to reduce system downtime and work in process inventory.

Given its affordable pricing and applicability to various DC/Logistics related

problems, the Arena simulation package would be the most appropriate option for

the Engineering teams within Gap Inc. However, for the purpose of this thesis,

Simul8 will be applied since the Thesis supervisor has provided access to the free

student version.

2.3 Line Balancing

Line balancing is a method of identifying optimal solutions through mathematical

calculations. It aims to efficiently distribute workload among a series of workstations

by taking into account various factors such precedence constraints, production rates

and objectives (i.e. minimize number of work stations or maximize productivity).

Line balancing problems of flow oriented operations such as BDC‟s Team Receiving

process is fairly difficult to solve. According to Driscoll and Thilakawardana [10], the

simplest form of an assembly line problem involves conveyor speed, cycle time at

each workstation, and series of sequential workstations. Complexities such as

probability distributions will further increase the difficulty of the problem. Though it

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will be difficult to determine a solution through such calculations, the concept of line

balancing can be applied through simulation testing to ensure workload is equally

distributed within a single receiving line.

3.0 Methodology Overview

Given the benefits and challenges associated with BPR, Simulation and Line

Balancing, this project entailed a combination of these techniques. The following set

of methods which are in compliance with the BPR approach, were applied over the

course of this project in order to evaluate and improve the Inbound area:

1. Build the Project Direction:

Conducted interviews with the Inbound manager and supervisors to

understand project expectations and critical success factors. Appendix A

details sample questions used during the interview;

2. Understand the Problem Scope

Observed and documented the current processes;

Collected data by reviewing documents or databases containing related

information;

Interviewed the supervisors to understand their current methods to meet

key performance metrics for Team Receiving and the OTS metric; and

Built an „As-Is‟ Simulation Model of Team Receiving, which takes into

account distributions related to workload variability, quantity of change

over and strategies applied by employees to reduce idle time;

3. Target the Problem

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Discussed potential root causes of problems related to Team Receiving

and the inability to meet the OTS metric among employees and

supervisors.

4. Design the Process

Identified potential new processes or strategies to overcome current

problems;

Tested and validated new approach to improve productivity for Team

Receiving by modifying the simulation model to take into account a new

line balancing strategy. The results were compared against the „As-Is‟

Model results; and

Presented a new process to overcome current problem of meeting OTS

metric to Inbound management and discussed the infrastructure alignment

necessary to support the change.

The scope of this project did not extend beyond these four sections of Business

Process Re-engineering. The BDC management team is responsible for planning

the implementation and actual implementation of the re-engineered processes into

the BDC operation.

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4.0 Process Description Development

This section details the current processes that were selected to be redesigned. An

understanding of these processes was necessary in order to identify root causes

during the problem analysis stage. In addition, the Team Receiving information was

employed to build an „As-Is‟ Simulation Model

4.1 Development of Team Receiving „As-Is‟ Simulation Model

The Team Receiving process is primarily required for sorting received cartons onto

pallets according to the style id after its product information had been uploaded into

the Warehouse Management System (WMS). Following palletization, the pallet is

slotted within a specific bulk storage location or unit pick modules prior to any

Outbound job function. Thus all cartons within the DC must be processed through

Team Receiving.

Through documentation and data collection, the necessary information related to the

Team Receiving sub-processes and workload variability was gathered to build a

sufficiently accurate „As-Is‟ simulation model for the purpose of this project.

4.1.1 Description of Current Team Receiving Sub-Processes

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BDC consists of four team receiving lines, where teams of four employees process

cartons from one trailer at a time. As shown in [Figure 1] and [Table 2], the process

consists of the following series of sub processes/ workstations:

1. Offload cartons: After opening the dock door and extending the moveable

conveyor near the edge of the door, an employee begins placing cartons on the

conveyor. In order to maintain efficiency throughout the line, he/she try their

best to group together cartons of the same purchase order (PO) and SKU.

2. SuperRAT (SRAT) station: At this workstation, carton information is uploaded

into WMS. Depending on the type of label and/or carton, this workstation

process and cycle time can vary in three different ways:

a. Manual Printing Process: Cartons from suppliers that do not comply with

Gap Inc‟s. labeling structure are relabeled with Veli Labels after data related

carton weight, style, size and quantity is entered into WMS for each carton.

b. Veli Scan Process: Non Full-Case1 cartons with Veli labels only require

scanning and its information is automatically uploaded into WMS.

c. One Step Process: Full-Case2 cartons with Veli labels only require the first

cartons to be scanned for each new SKU.

If it is the first carton of any SKU, employees are required to conduct a First

Carton Seen Screen. This sub process requires opening the first carton of the

new SKU, verifying its contents and entering data related to PO, size, weight,

style, and quantity.

1 Non Full-Case cartons consist of units with multiple sizes of the same product. These cartons are not

processed through Unit Picking where cartons are opened and one or two units are sent in an order to the store. 2 Full Case cartons consist of units with the same product and size. They are sent directly to the store as a whole

entity when they stock their shelves with new products. They are not opened within the DC.

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If there are any discrepancies with the contents, three cartons are sent to

Vendor Auditing. In addition, if the PO is from a supplier that is on the Vendor

Audit list, three cartons are also sent to the Vendor Auditing.

3. Palletize cartons: At this workstation, cartons are palletized with respect to style

id. Once a pallet reached its maximum height, the set of cartons are updated in

the system as either: pure (one style), side by side (2 styles) or mixed (more

than 2 styles) pallet.

Prior to processing a shipment, a member of the team picks up a sheet from the

Inbound office which details dock door number, number of cartons, number of POs

and number of SKUs. This information can provide an idea of the workload level for

each trailer.

As the number of SKUs increase in a single trailer, the amount of First Carton Seen

Screen increases and thus the workload increases to process the trailer. However,

the information does not give a complete picture of the workload. Each trailer can

consist of multiple POs where each PO will require one of the three SRAT station

sub-processes to upload carton information into WMS. Unfortunately, teams do not

have visibility of the percentage breakdown of Manual Printing, Veli Scan and One

Step for each trailer. However, over the course of a week or month, the percentage

breakdown is fairly consistent where Manual Printing (i.e. the most time consuming

upload process) does not exceed 12%.

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Therefore, the team usually assigns one employee to each sub-process/workstation

except for the SRAT station. An additional employee is positioned at the 2nd SRAT

station since a significant proportion of its variable workload has a higher cycle time

(i.e First Carton Seen Screens) than the other workstations. However, if the

additional employee notices a large queue (on average more than 65 cartons)

forming on the conveyor line leading to the palletization area, he/she walks over to

the end of the line to assist the Palletizer.

4.1.2 Description of „As-Is‟ Model

Given the data sources [Appendix B] and the information detailed in 4.1.1, an „As-Is‟

simulation model [Figure 2] was created using Simul8. The following set of

parameters or assumptions were built into the model:

1. Conveyor speed of 25 feet per minute;

2. Conveyor length of 50 feet leading to the SRAT station from the dock door

and conveyor length of 135 feet leading to the Palletization from the SRAT

station;

3. Carton/Work type dimensions of 24” x 24” for all cartons except Full Case

cartons. Full case cartons are 12” x 24”;

4. The time to perform the three main activities under Team Receiving based on

Maynard Operation Sequence Technique (MOST)/ Expectation values [Table

2]: Offloading, SRAT and Palletization. However, palletization is peformed

twice as fast for Full Case cartons since they are palletized two at a time;

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5. There is a continuous flow of cartons and therefore there is no account for

downtime related to opening/closing dock doors or any other initial set up

activities. The time spent performing these activities are recorded under

indirect hours and thus outside the scope of improving Team Receiving

productivity metric;

6. The time to perform 1st Carton Seen Screens based on MOST/Expectation

values every time the SKU changes

7. The Offloader places all cartons with the same PO and SKU on the conveyor

before changing to a new SKU or PO;

8. One resource is assigned to each work station (Offloader, SRAT Stations and

Palletizer workstations). The fourth resource floats between the SRAT Station

2 and Palletizer 2 depending on the number of cartons waiting to be

palletized. If the conveyor (leading to Palletization) carton quantity exceeds

65, the fourth resource walks over to the area to palletize. Once the conveyor

carton quantity drops below 30, it walks back to the second SRAT station to

resume work there;

9. Travel time between SRAT Station 2 and Palletizer 2 is 2 minutes. This travel

time also includes computer sign-in time;

10. Every PO is processed as either Manual Printing, Veli Scan or One Step at

the SRAT station;

11. Probability distributions related to POs per Trailer [Figure 3] and SKUs per

PO [Figure 4] which was derived from information gathered on Inbound team

sheets [Figure 5];

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12. Probability distribution related to Cartons per SKU [Figure 6] which was

derived from Team Receiving Business Objects report [Table 4];

13. Percentage breakdown of Manual Printing cartons, Veli Scan cartons and

One Step cartons as shown in Figure 7 which was derived from data provided

by Labor Management System [Table 5].

According the model after six runs [Table 6], the current average productivity rate is

73 CPDH which is fairly close last year‟s performance of 69 CPDH. Since the model

does not take into account the impact of training new employees and infrequent

downtimes related to vendor audit problems, the outputted productivity rate is

reasonable and validates the accuracy of the model.

4.2 Description of OTS Metric Management

In terms of attempting to meet the OTS metric, the Inbound team simply tries to work

through as many shipments as possible within a given day in a First–In-First-Out

(FIFO) manner. Given the supervisor‟s time constraints of managing a large team,

the task of assigning each shipment to a team‟s dock door is managed by Inbound

clericals who check-in the shipments as they enter the yard.

Airfreight shipments usually arrive on Friday afternoons. Since BDC does not run on

Saturdays and these shipments need to be stocked within two days instead of three

days, it is processed as soon as it arrives. Thus, these shipments do not usually

miss the stocking deadline.

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5.0 Problem Analysis

Overall, Inbound has two major problems:

Easier workloads decrease Team Receiving efficiency

Within Team Receiving, there is a large variation in workload from shipment to

shipment. The largest impact on workload level is the quantity of First Carton Seen

Screens (i.e. changeover). Though productivity is expected to increase

proportionally to the quantity of changeover, this was not evident from observations

of the actual process or the results outputted by the „As-Is‟ model.

Figure 8: Current Team Receiving Productivity

Team Receiving Productivity

60.00

62.00

64.00

66.00

68.00

70.00

72.00

74.00

76.00

78.00

80.00

1 3 5 7 9 11

Cartons to First Carton Seen Screens

CP

DH

Four Man Team

As shown in [Figure 8], as the ratio of Cartons to First Carton Seen Screens

increases, productivity increases; however, it begins to plateau as the ratio becomes

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greater than 7. Through observations, it is now understood that as the workload

decreases, employees at the SRAT station either slow down due to a conveyor

blockage or continuously walk between the SRAT station and Palletization area in

order to balance issues related to conveyor blockage or waiting time of the

Palletizer. Therefore with easier workloads, Team Receiving lines are poorly line

balanced.

Lack of information related to stocking deadlines

Following consolidation, the supervisors assumed that Inbound‟s inability to meet the

OTS metric was due to poor Team Receiving productivity. However, despite a

significant improvement in productivity and shipment throughput per shift in the

months following consolidation, Inbound was still unable to meet its OTS metric for

20% of its shipments.

As a result, a meeting was held with the Inbound manager, supervisors and WMS

coordinator to re-evaluate the current FIFO strategy. Through the discussion, it was

acknowledged that some of the shipments could possibly be arriving late and

therefore shortening the time available to meet the stocking deadline set

automatically by one of Gap‟s Logistics Management systems. Although some of

supervisors realized the need to prioritize shipments with respect to stocking

deadlines, they did not pursue the idea since they did not have information related to

stocking deadlines readily available to them. In order to gain visibility of these

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deadlines, large amounts of data mining was required. However, the team did not

have the resources necessary to take on such a time consuming task each day.

6.0 Process Redesign Development

This section details the new processes/strategies designed to overcome the

problems specified in section 5.0 and how they were developed.

6.1 Redesigning Team Receiving Process

Since teams of four employees (i.e. Four Man Teams) generates inefficiencies for

easier workloads (i.e. low quantity of Cartons to First Seen Screens), the application

of Three Man Teams (i.e. teams of three employees) was initiated to process such

shipments.

6.1.1 Simulation Testing Objectives and Procedures

The purpose of the simulation testing was to determine the feasible conditions to

utilize Three Man teams instead of Four Man teams to increase the level of

productivity. Since the percentage of First Carton Seen Screens significantly affects

the workload for each shipment, this testing aimed to determine the threshold ratio of

Cartons to 1st Carton Seen Screens at which the Inbound Team could feasibly utilize

Three Man Teams. This information could then be applied easily by the Inbound

clericals who will use the threshold ratio to route „easy‟ shipments to preset Three

Man Teams and the other shipments to preset Four Man Teams.

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In order to achieve this objective, the „As-Is‟ simulation model was modified to

calculate the ratio of Cartons to 1st Carton Seen Screens for every trailer arrival. If

the ratio was greater than the ratio value being tested (i.e. 1, 2, 3, 4, etc), three

employees are used to process the trailer instead of the usual four employees.

Appendix C details the code utilized to achieve this approach. Since the number of

cartons per SKU follows the Geometric probability distribution (parameter = 0.25),

the ratio rarely exceeded 17 and thus the model was run only 17 times.

For each ratio value, the model was run for more than four or five runs where each

run replicated the arrival of more than 500 shipment arrivals for a single receiving

lane. This was done to ensure that the ratio was tested against a wide range of

trailer arrival scenarios.

Following each run, the program returned data related to the number of units

processed through Three Man Teams and the time spent to process its units in

addition to the number of units processed through Four Man Teams and the time

spent to process its units (sample information outputted by the model is detailed in

Table 7).

6.1.2 Results & Recommendations

According to the simulation testing results [Figure 9], it is feasible to utilize Three

Man teams if the ratio of Cartons to 1st Carton Seen Screens is greater than 5. The

application of this threshold ratio will increase productivity up to 42% for each

shipment.

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Figure 9: Summary of Three Man Team Test Results

Three Man Teams vs. Four Man Teams

55.00

60.00

65.00

70.00

75.00

80.00

85.00

90.00

95.00

100.00

105.00

1 3 5 7 9 11 13 15 17

Cartons to First Carton Seen Screens

CP

DH

Current ( without

Three Man

Team Scheme)

Three Man

Team

There will be a significant jump in productivity following the application of Three Man

teams mainly because the productivity rate of a single SRAT station will become

fairly equivalent to the productivity rate of a single Palletizer as the ratio increases.

Under such circumstances of a well balanced receiving line, the overall productivity

will improve due to the elimination of inefficiencies related to waiting for cartons or

conveyor overload.

Although the application of the Three Man Team scheme will improve productivity

under its optimal conditions, the total cycle time (CPDH x number of associates on a

team) to complete each shipment increases by up to 25% (drop from 292 CPH to

219 CPH). If the OTS metric is being well managed, it should not be a major

problem to the other key performance indicators. However, if a shipment is at risk of

If Ratio >5, Three Man Team will improve productivity

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meeting its „On Time to Stock‟ metric, it is recommended not to utilize a Three Man

team to receive it.

6.2 Redesigning OTS metric management process

Following discussions with external engineers in other DCs within North America, it

was understood that the best way to increase visibility of stocking deadlines given

resource constraints was to increase communication between the Inbound team and

the local Transportation team. The Transportation team who were responsible for

the management of trailers across Canada, kept daily records of information related

to incoming and outgoing BDC shipments. Since both teams had different

management systems, this information was not readily available to the Inbound

team.

In order to achieve the goal of meeting the OTS metric, a meeting was held with the

Transportation manager and Inbound manager to discuss a new process to break

down current infrastructure restrictions. Fortunately, the Transportation manager

agreed to support the Inbound team since his team already data mines such

information for performance measurement needs. Furthermore, it would be a

duplication of work if the Inbound team took on this task as well. Thus, the new

process required that one of the Transportation team members send an Excel sheet

[Table 8] containing important information related to trailers in the yard on a daily

basis. Once the supervisors receive this sheet, they are required to prioritize trailers

with respect to their deadlines.

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This process has been in place since December 2006. For the month of February,

only 5% of the shipments missed the stocking deadlines and thus the „OTS‟ metric is

on target.

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7.0 Conclusion

Overall, this thesis project was able improve BDC Inbound team‟s ability to meet key

performance metrics related to OTS metric management and Team Receiving

productivity. Through the application of BPR techniques, core challenges and

infrastructure restrictions related to the OTS metric were easily identified and

resolved by increasing communication between segregated teams. In addition,

through simulation modeling and an understanding of line balancing, a new strategy

to improve Team Receiving productivity by up to 40% per shipment was created and

tested.

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7.0 References

[1] Bush, B. 2001. Productivity Improvement Through Business Process Reengineering. Handbook of Industrial Engineering, Maynard‟s Industrial Engineering Handbook, pp. 2.11-2.27.

[2] K.Concannon, M. Elder, K. Hunter, J. Tremble, S. 2004. Tse. Introduction to

Simulation. Simulation Modeling with Simul8. pp. 15-31 [3] J. Driscoll, D. Thilakawardana. 2001. The definition of assembly line balancing

difficulty and evaluation of balance solution quality. Robotics and Computer-Integrated Manufacturing, 17, 81-86.

[4] Swain, J. 2005. Gaming Reality. OR/MS Today, pp. 1-6. [5] R.Phelps, D. Parsons, A. Siprelle. 2001. SDI Supply Chain Builder: Simulation

from atoms to enterprise. Winter Simulation Conference Proceedings, 1, 246-249.

[6] E. Gelenbe, H. Guennouni. 1991. Flexism: A flexible manufacturing system

simulator. European Journal of Operational Research, 53, 149- 165. [7] J. Kemers, Y. Merkayer. 1991. Simulation application of logistics strategy

planning in the Baltic IT market. European Simulation Symposium, 11, 2004- 208.

[8] Forcino, H. 2000. Warehouse Simulation creates a new model for change.

Managing Automation, 15, 61-62. [9] L. Contreras, C. Modi, A. Pennathur. 2005. Integrating simulation modeling

and equipment condition diagnostics for predictive maintenance strategies- case study. Proceedings of the 2002 Winter Simulation Conference, 2, 1289-1296.

[10] Kempfer, Lisa M. 2005. Top 5 Reasons to Use Warehouse Simulation

Software. Material Handling Management, 60, 5:33-34.

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8.0 Appendices Appendix A: Sample Interview Questions

During an initial group meeting with supervisors, the following set of questions was

discussed:

1. What are the key performance metrics for the Inbound team?

2. What challenges do you face in meeting this performance metrics?

3. What strategies do you apply in meeting each of these key

performance metrics?

4. How do you manage your employees and assign them duties?

5. What are the possible root causes of the productivity drop?

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Appendix B: Data Sources for Team Receiving „As-Is‟ Model

The following are the main data sources that were used in building the As- Is

Simulation Model:

1. [Table 3] Maynard Operations Sequencing Technique (MOST) standards: MOST

is a method of determining the elemental time necessary to complete each task

in an activity. These documents provided expected cycle time for each

workstation/sub-process.

2. Labor Management System Database: This database keeps an accumulated

track of all important units of measure for a particular job function such as

number of Cartons, SKUs, First Carton Seen Screens, Manual Printing Cartons,

Veli Scan Cartons, etc. This set of information helped to build probability

distributions related to workload variability.

3. Team Receiving Business Objects Report: The Business Objects software is

linked with the Warehouse Management System and thus its report provides a

time stamp of every carton processed through SRAT station with information

related to employee id, receiving line, SKU number and etc.

4. Inbound Team Sheets [Figure 5]: Prior to processing a shipment, a member of the

team picks up a sheet from the Inbound office which details dock door number,

number of cartons, number of POs and number of SKUs.

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Appendix C: Three Man Testing Visual Logic Code

VL SECTION: Blocker Route In Before Logic

Begin IF int_SKU count = 0 Begin IF int_PO count = 0 Begin IF int_CTNcount = 0 Begin IF int_CALCTNcount/int_CALSKU count > 6 Begin SET SRATor Palletizer Associate.Max Available = 0 SET TeamQty = 3 End ELSE Begin SET SRATor Palletizer Associate.Max Available = 1 SET TeamQty = 4 End End End End End

VL SECTION: PO Batch Route In After Logic

Begin IF TeamQty = 4 Begin SET Total4Units = Total4Units+int_CALCTNcount SET TotalLaborUnits = TotalLaborUnits+int_CALCTNcount SET TimetoComplete = EndTime-StartTime SET Fourman Minutes = TimetoComplete*4 SET Total4Minutes = Total4Minutes+Fourman Minutes SET TotalLaborMinutes = TotalLaborMinutes+Fourman Minutes End IF TeamQty = 3 Begin SET Total3Units = int_CALCTNcount+Total3Units SET TotalLaborUnits = TotalLaborUnits+int_CALCTNcount SET TimetoComplete = EndTime-StartTime SET Threeman Minutes = TimetoComplete*3 SET Total3Minutes = Total3Minutes+Threeman Minutes SET TotalLaborMinutes = TotalLaborMinutes+Threeman Minutes End SET int_PO count = 0 SET int_SKU count = 0 SET int_CALSKU count = 0 SET int_CTNcount = 0 SET int_CALCTNcount = 0 SET StartTime = Simulation Time Set Route In Discipline Blocker , Passive End

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9.0 Figures

Figure 1: Team Receiving High Level Process Map

Offload Cartons

SuperRAT station

Palletize Cartons

Veli Scan Process

Manual Printing Process

One Step Process

First Carton Seen Screen Process

New SKU?

No

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Figure 2: Team Receiving Simulation Model

Dummy Workstations

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Figure 3: Probability Distribution of POs per Trailer

Comparison of Input Distribution and Geomet(0.11)

Values in 10^1

0.0

0.2

0.4

0.1 2.6 5.1 7.5 10.0 12.5

Input

Geomet

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Figure 4: Probability Distribution of SKUs per PO

Comparison of Input Distribution and NegBin(3.00,0.35)

Values in 10^1

0.0

0.1

0.2

0.1 0.7 1.3 1.9 2.5 3.1

Input

NegBin

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Figure 5: Sample Inbound Team Sheet

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Figure 6: Probability Distribution of Cartons per SKU

Comparison of Input Distribution and Geomet(0.25)

Values in 10^1

0.0

0.2

0.5

0.1 1.8 3.5 5.3 7.0 8.7

Input

Geomet

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Figure 7: Probability Breakdown of SRAT station sub-processes

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10.0 Tables Table 2: Expected Cycle Time of Team Receiving Workstations

Workstation Workstation sub process

Cycle Time (s) *

Unit of Measure Cycle Time Accounts for:

Offloading 8.05 Carton

Time for Unloading each carton. Also accounts time necessary to open trailer door, extending mobile conveyor into trailer, etc

SRAT

Manual Printing 23.38 Carton Time for printing new labels and scanning each cartons

Veli Cases 8.99 Carton Time spent scanning each carton

First Carton Seen Screens 77.55 Carton

Time for completing a First Carton Seen Screen

Palletization

Palletize 15.11 Carton Time for palletizing each cartons

Build Pallet 52.88 Pallet Time for creating a new pallet and updating the WMS system

* Cycle time is based on Maynard Sequence Operation Technique (MOST), which is used to determine the expected time to complete a series of steps.

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Table 3: Sample MOST Expectation Document 1501 INBOUND - OFFLOAD TRAILER (TR HUM) (DLX)

Task UOM TMU FREQ TOTAL

2 OPEN DOCK DOOR, ATTACH MANUAL DOCK LEVELER * * * *

3

WALK 11 - 15 STEPS TO EXTENSION CONVEYOR STORAGE - 2 PERSON TRAILER 240 2 480

4

PUSH EXTENSION CONVEYOR 10-13 STEPS TOTRAILER - 2 PERSON TRAILER 240 2 480

5 ATTACH CONVEYOR - 2 PERSON TRAILER 460 2 920

6 *FREQ* GET KNIFE TRAILER 20 0.77 15.4

7 *FREQ* CUT STRETCH WRAP FROM PALLET TRAILER 210 0.77 161.7

8 WALK 1-2 STEPS TO CARTON CARTON 30 1 30 9 READ P.O NUMBER (7 DIGITS) CARTON 100 1 100

10 GET BULKY CARTON W/O REACH AND PLACEMENT CARTON 30 0.5 15

11

BEND 50%, GAIN CONTROL OF BULKY OBJECT W/O REACH AND PLACEMENT CARTON 60 0.5 30

12 WALK 1-2 STEPS TO END OF CONVEYOR CARTON 30 1 30

13 PLACE CARTON ONTO CONVEYOR W/ ADJUSTMENT CARTON 30 1 30

14 ADJUST EXTENSION CONVEYOR - PERSON TRAILER 90 15 1350

15 CLOSE DOCK DOOR, DETACH MANUAL DOCK LEVELER * * * *

16 --- END OF WORK --- * * * *

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Table 4: Sample Team Receiving Business Objects Report

OPID DATE_WMS TO_LOC TO_LOAD_ID TO_QTY SUBSTR CASE_ID WSKUSKU PK Factor

100140 2007010213152580 R10-01-1-M 30501700 0 R10 4200150085934640 97478760000 8

100140 2007010513302110 R10-01-1-M 30588469 0 R10 4200150086227740 1114404240002 100

100140 2007010809292870 R10-01-1-M 30612015 0 R10 4200150086314050 2649391540000 360

100140 2007010510175480 R08-01-1-1 30585772 0 R08 4200150086221160 3544060143532 18

100140 2007010915521720 R10-01-1-M 30648356 0 R10 4200150086466940 4491470040000 10

100140 2007010915522630 R10-01-1-M 30648364 0 R10 4200150086466960 4491470040000 10

100140 2007010915523700 R10-01-1-M 30648369 0 R10 4200150086466970 4491470040000 10

100140 2007010915524900 R10-01-1-M 30648378 0 R10 4200150086466980 4491470040000 10

100140 2007010915525940 R10-01-1-M 30648392 0 R10 4200150086467000 4491470040000 10

100140 2007010915530490 R10-01-1-M 30648397 0 R10 4200150086467010 4491470040000 10

100140 2007010915531170 R10-01-1-M 30648408 0 R10 4200150086467030 4491470040000 10

100140 2007010915532030 R10-01-1-M 30648421 0 R10 4200150086467040 4491470040000 10

100140 2007010915532630 R10-01-1-M 30648427 0 R10 4200150086467050 4491470040000 10

100140 2007010915533190 R10-01-1-M 30648433 0 R10 4200150086467060 4491470040000 10

100140 2007010915534720 R10-01-1-M 30648447 0 R10 4200150086467080 4491470040000 10

100140 2007010915541410 R10-01-1-M 30648453 0 R10 4200150086467100 4491470040000 10

100140 2007010915542110 R10-01-1-M 30648457 0 R10 4200150086467120 4491470040000 10

100140 2007010915543090 R10-01-1-M 30648461 0 R10 4200150086467130 4491470040000 10

100140 2007010916185530 R10-01-1-M 30648963 0 R10 4200150086467480 4491470040000 10

100140 2007010916190430 R10-01-1-M 30648970 0 R10 4200150086467490 4491470040000 10

100140 2007010916191870 R10-01-1-M 30648985 0 R10 4200150086467510 4491470040000 10

100140 2007010916192450 R10-01-1-M 30648992 0 R10 4200150086467530 4491470040000 10

100140 2007010916192980 R10-01-1-M 30649000 0 R10 4200150086467540 4491470040000 10

100140 2007010916193600 R10-01-1-M 30649006 0 R10 4200150086467560 4491470040000 10

100140 2007010916194380 R10-01-1-M 30649013 0 R10 4200150086467570 4491470040000 10

100140 2007010916195050 R10-01-1-M 30649014 0 R10 4200150086467580 4491470040000 10

100140 2007010916195470 R10-01-1-M 30649018 0 R10 4200150086467600 4491470040000 10

100140 2007010916200070 R10-01-1-M 30649021 0 R10 4200150086467610 4491470040000 10

100140 2007010916200620 R10-01-1-M 30649026 0 R10 4200150086467640 4491470040000 10

100140 2007010916201280 R10-01-1-M 30649029 0 R10 4200150086467650 4491470040000 10

100140 2007010916202150 R10-01-1-M 30649030 0 R10 4200150086467660 4491470040000 10

100140 2007010916202710 R10-01-1-M 30649034 0 R10 4200150086467670 4491470040000 10

100140 2007010916441540 R10-01-1-M 30649589 0 R10 4200150086468020 4491470040000 10

100140 2007010916442430 R10-01-1-M 30649595 0 R10 4200150086468040 4491470040000 10

100140 2007010916442990 R10-01-1-M 30649598 0 R10 4200150086468050 4491470040000 10

100140 2007010917085570 R10-01-1-M 30649934 0 R10 4200150086468400 4491470040000 10

100140 2007010918074260 R10-01-1-M 30650706 0 R10 4200150086469620 4491470040000 10

100140 2007010918075090 R10-01-1-M 30650709 0 R10 4200150086469640 4491470040000 10

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Table 5: Sample Team Receiving Labour Management System report

Production KVI Data

12/16/2006 1/11/2007

Job Code Perf % Goal Direct KVI 03 KVI 04 KVI 05 KVI 06 KVI 07 KVI 08 KVI 09

1501 64 2,996 4,670 277103 0 22,168 289731 91443 15998

KVI 10 KVI 11 KVI 13 KVI 14 KVI 15

174349 22168 163490

KVI Description

KVI 3 Cartons Palletized

KVI 4 Sku

KVI 6 SuperRat Cases

KVI 7 Exploded Units

KVI 8 1-Step Cartons

KVI 9 Pallets

KVI 10 Case Weight

KVI 11 First Case Seen

KVI 15 1-Step Cases

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Table 6: „As-Is‟ Simulation Model Results Simulation Object

Performance Measure Run 1 2 3 4 5 Average

Offloader Waiting % 0.03278 0.15161 0.03128 0.1577 0.09997 0.094668

Working % 86.69753 86.87443 86.99494 87.1632 86.88206 86.92243

Blocked % 13.26969 12.97396 12.97378 12.6791 13.01797 12.9829

SRAT Station Waiting % 16.32414 16.36898 16.87816 17.25602 16.13413 16.59229

Working % 24.3416 24.09381 23.44368 23.35673 23.94651 23.83647

Blocked % 4.85288 4.97331 4.8537 4.89923 4.94607 4.905038

Change Over % 54.48138 54.5639 54.82445 54.48802 54.97329 54.66621

SRAT Station 2 Waiting % 50.83412 51.42654 51.85353 52.00864 50.64957 51.35448

Working % 46.64142 46.17153 45.57976 45.47755 46.86788 46.14763

Blocked % 2.52446 2.40193 2.56671 2.51381 2.48255 2.497892

Change Over % 0 0 0 0 0 0

Palletizer 2 Waiting % 71.53782 70.98647 71.70417 71.52087 71.02238 71.35434

Working % 28.46218 29.01353 28.29583 28.47913 28.97762 28.64566

Blocked % 0 0 0 0 0 0

Palletizer Waiting % 25.0557 24.98515 24.96942 24.91864 24.89988 24.96576

Working % 74.9443 75.01485 75.03058 75.08136 75.10012 75.03424

Blocked % 0 0 0 0 0 0

Total3Minutes Value 0 0 0 0 0

Total3Units Value 0 0 0 0 0

Total4Minutes Value 115013.2 114709.2 115041.1 114722 114964 574449.5

Total4Units Value 139381 139567 139841 140113 139776 698678

72.71 73.00 72.93 73.28 72.95 72.98

TotalLaborMinutes Value 115013.2 114709.2 115041.1 114722 114964

TotalLaborUnits Value 139381 139567 139841 140113 139776

MP Items Entered 15670 14760 14598 14354 15107

0.11 0.11 0.10 0.10 0.11

Veli Final Items Entered 46319 48269 46518 46875 47834

One Step Final Items Entered 77460 76694 78789 78952 76794

Final Queue

Number Completed Jobs 139449 139723 139905 140181 139735

SRATor Palletizer Associate Traveling % 0.28873 0.28958 0.29063 0.29224 0.29125

Four Man CPDH 72.98

Three Man CPDH 0

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Table 7: Sample Three Man Team Simulation Test Results

Simulation Object Performance Measure Run 1 2 3 4 5

Offloader Waiting % 0.02317 0.00994 0.07886 0.08344 0.0729

Working % 58.01301 59.30255 59.83296 57.49318 59.249

Blocked % 41.96382 40.6875 40.08818 42.42338 40.6781

SRAT Station Waiting % 2.63255 2.74635 2.97012 2.52893 2.46324

Working % 34.68204 33.95568 33.93986 35.38457 33.93522

Blocked % 5.97616 6.19826 6.26414 5.86598 6.23882

Change Over % 56.70926 57.09971 56.82588 56.22052 57.36272

SRAT Station 2 Waiting % 97.30526 96.97084 96.60571 97.04351 96.78882

Working % 2.62834 2.95312 3.31882 2.89083 3.1341

Blocked % 0.06639 0.07604 0.07547 0.06566 0.07708

Change Over % 0 0 0 0 0

Palletizer 2 Waiting % 99.25966 99.19672 98.99663 99.2177 98.99796

Working % 0.74034 0.80328 1.00337 0.7823 1.00204

Blocked % 0 0 0 0 0

Palletizer Waiting % 40.84449 39.87945 39.53474 41.06712 39.95701

Working % 59.15551 60.12055 60.46526 58.93288 60.04299

Blocked % 0 0 0 0 0

Total3Minutes Value 83116.78 82449.01 82225.77 82640.47 82078.66


63.70 65.10 65.61 63.14 65.02

Total4Minutes Value 4240.534 4823.061 5271.56 4595.519 5076.184


71.76 70.80 71.07 70.52 70.51

TotalLaborMinutes Value 87357.32 87272.07 87497.33 87235.99 87154.84

TotalLaborUnits Value 93310 95144 96162 92368 94916

MP Items Entered 9883 9550 9592 10402 9529

0.11 0.10 0.10 0.11 0.10

Veli Final Items Entered 31247 31688 31791 31184 31789

One Step Final Items Entered 52174 54144 54804 50852 53975

Final Queue

Number Completed Jobs 93304 95382 96187 92438 95293

SRATor Palletizer Associate Traveling % 0.28824 0.27305 0.3177 0.25538 0.3159

Four Man CPDH 70.91

Three Man CPDH 64.51

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Table 8: Sample Inbound Trailer Log

BDC Inbound Trailer Log

Wednesday, January 10, 2007

Total Cartons On Site: 10,374

Carrier Trailer # Status Dock Door

DATE Ctns Mode PO's

Earliest Plan INDC date

Time if AIR

Planned Stocked + 3 days

Air <2days

Priority

PAUL'S NYKU604928 FULL 14 9-Jan 476 OCEAN 2 8-Jan 1/11

MTR 51248 IP 15 9-Jan 1131 OCEAN 23

8-Jan 1/11

PAUL'S NYKU605314 FULL 16 9-Jan 934 OCEAN 30 9-Jan 1/12

PAUL'S APHU450471 IP 17 8-Jan 820 OCEAN 9 7-Jan 1/10

BTT CMBU236585 IP 18 9-Jan 279 OCEAN 2

7-Jan 1/10

PAUL'S APLU464550 FULL 19 8-Jan 968 OCEAN 5

7-Jan 1/10

PAUL'S APLU462427 IP 20 8-Jan 733 OCEAN 4

9-Jan 1/12

MTR 51217 IP 21 9-Jan 906 OCEAN 19

9-Jan 1/12

BLUE LINE 7285 FULL YARD 10-Jan 943 MOTOR 9

9-Jan 1/12

PAUL'S NYKU602900 FULL YARD 10-Jan 916 OCEAN 11

13-Jan 1/16

BTT TTNU219555 FULL YARD 9-Jan 207 OCEAN 3 12-Jan 1/15

PAUL'S TRLU413320 FULL YARD 9-Jan 682 OCEAN 13 10-Jan 1/13

PAUL'S TEXU464275 FULL YARD 10-Jan 656 OCEAN 1

11-Jan 1/14

BTT TTNU219555 FULL YARD 9-Jan 207 OCEAN 3 10-Jan 1/13

PAUL'S APZU402007 FULL YARD 10-Jan 262 OCEAN 4

13-Jan 1/16

PAUL'S APHU450471 FULL YARD 10-Jan 254 OCEAN 31 11-Jan 1/14

SMURFIT 20395 FULL YARD 4-Jan

SMURFIT 20219 FULL YARD 5-Jan

? 138 YARD 4-Jan PALLETS

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