RELAYOUT OF A MANUFACTURING FACILITY WITH SAFETY

CONSIDERATIONS

Shamaya Morris

Problem Report submitted to the

Benjamin M. Statler College of Engineering and Mineral Resources

at West Virginia University

in partial fulfillment of the requirements for the degree of

Master of Science

Industrial Engineering

Alan McKendall, Ph.D., Chair

Ashish Nimbarte, Ph.D.

Don Stewart M.S., TMMWV

Department of Industrial & Management Systems Engineering

Morgantown, West Virginia

2016

Keywords: Facility Layout Planning, Unequal-Area Facilities, Mixed Integer Linear

Programming Models,

Copyright 2016 Shamaya Morris

ABSTRACT

RELAYOUT OF A MANUFACTURING FACILTY WITH SAFETY

CONSIDERATIONS

Shamaya Morris

This study investigates layout options for the machining department of the transmission production

area of the Toyota Motor Manufacturing West Virginia (TMMWV) plant in Buffalo, WV.

TMMWV is making modifications to one of its products. The current layout has a combination of

2 different types of machines used for machining of the existing model, model type A and model

type B. For the production of the new model, the model A machines will be reused, which will

require the removal of all model B machinery. This will require a re-layout of the machining area.

As a result, the goal of this project is to provide TMMWV layout proposals, of which includes

only the machinery for model type A. Of the provided proposals, an optimal or “ideal” layout as

well as practical layouts will be pursued, with the objective of minimizing material handling cost

while considering safety issues. This problem is defined as the unequal-area facility layout

problem (FLP), which determines the positions of unequal-area facilities (e.g., departments, cells,

machines) on the continuous plant floor. A mixed integer linear programming (MILP) model is

presented for the FLP and is solved using the CPLEX solver. Layouts for each of the three

departments within the machining area and two layout alternatives for the overall layout of the

machining area were obtained for the TMMWV plant. Overall layout option 2 had a 61.8%

improvement over the overall layout option 1 with respect to the objective of minimizing total

distance parts travel.

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DEDICATION

I would like to dedicate this study to my entire family. Through every change, loss and

heartbreak we’ve emerged even closer than ever. Thank you for the encouragement, love and

support.

iv

ACKNOWLEDGEMENTS

To Dr. McKendall, thank you so much for your consistent patience and encouragement. I

couldn’t have imagined going through this process without you. Your time spent helping me

become a better student has is the greatest contribution possible. My deepest and most sincere

“Thank you”.

I wish to thank the entire IMSE for every year of my time here. Undergraduate was an

unbelievable journey, and now I can say the same for my graduate studies. I appreciate the votes

of confidence, every encouraging word and the many different ways they went above and

beyond to assist me with whatever I needed. This has truly been the difference maker in my

academic career.

I would like to sincerely express my deepest gratitude to Don Stewart and everyone at

Toyota Motor Manufacturing plant in Buffalo, WV. This project definitely wouldn’t have been

possible without you! Thank you so much for the wonderful opportunity of participating in the

Co-Op program. The experience and lessons learned have helped me to become the engineering

professional I’ve always envisioned. Thank you!

Lastly to my committee members: Dr. McKendall, Dr. Nimbarte and Don Stewart. Thank

you so much for your patience with me during this process. My deepest expression of gratitude

for your time and understanding. Thank you!

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TABLE OF CONTENTS

ABSTRACT ......................................................................................................................................................... i

DEDICATION .............................................................................................................................................. i

ACKNOWLEDGEMENTS ........................................................................................................................ ii

LIST OF FIGURES ................................................................................................................................... iv

LIST OF TABLES ..................................................................................................................................... iv

CHAPER 1: INTRODUCTION ................................................................................................................. 1

1.1 Introduction ........................................................................................................................................... 1

1.2 Problem Definition ................................................................................................................................ 4

1.3 Research Objectives .............................................................................................................................. 5

1.4 Organization .......................................................................................................................................... 5

CHAPTER 2: BRIEF LITERATURE REVIEW ..................................................................................... 6

2.1 Literature Review .................................................................................................................................. 6

CHAPTER 3: PROBLEM STATEMENT AND METHODOLOGY ..................................................... 8

3.1 Problem Statement ................................................................................................................................ 8

3.2 Methodology ........................................................................................................................................ 12

3.3 Data ...................................................................................................................................................... 15

CHAPTER 4: COMPUTATIONAL RESULTS AND CONCLUSIONS ............................................. 18

4.1 Data and Discussion ............................................................................................................................ 18

4.2 Safety Considerations ......................................................................................................................... 21

4.3 Conclusive Remarks and Future Research ....................................................................................... 21

References .................................................................................................................................................. 23

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LIST OF FIGURES

Figure 1.1a ................................................................................................................................................... 2

Figure 1.1b ................................................................................................................................................... 2

Figure 3.1 ..................................................................................................................................................... 8

Figure 3.2 ..................................................................................................................................................... 9

Figure 3.3 ................................................................................................................................................... 10

Figure 3.4 ................................................................................................................................................... 11

Figure 4.1 ................................................................................................................................................... 18

Figure 4.2 ................................................................................................................................................... 19

Figure 4.3 ................................................................................................................................................... 19

Figure 4.4 ................................................................................................................................................... 20

Figure 4.5 ................................................................................................................................................... 20

LIST OF TABLES

Table 3.1 ..................................................................................................................................................... 15

Table 3.2 .......................................................................................................................................... 16

1

CHAPER 1: INTRODUCTION

1.1 Introduction

Facility re-layout is becoming more and more frequent as many industrial settings and

manufacturing facilities are changing over time to include expanses in production systems and/or

product modification. Changes in any layout are most often brought about due to fluctuations in

the production flow (an increase or decrease in customer demand), changes in the design of the

current product, products added or removed from the production schedule, and/or shortened

product life cycles (McKendall et al., 2010). Planning is an essential component to ensuring a

facility’s continuing and effective production activity. One of the objectives of any existing

facility modification is to decrease the number of days the facility has to halt production in order

to achieve the desired changes (i.e. to reduce loss of production costs), which makes layout

planning an imperative necessity for efficiency. Additional objectives, just as important, are the

reduction of rearrangement costs (the cost incurred to relocate machine(s) from one location on

the plant floor to another) as well as material handling costs. The facility layout problem (FLP) is

determining the assignment of facilities (e.g. cells, machines, or departments) on the plant floor

in such a way that minimize material handling costs. In some case, the objective may also be to

maximize adjacency or closeness of pairs of facilities.

The layout alternatives or designs generated from the FLP will be a direct derivative of

the time spent planning. As stated above, it is especially crucial that considerable time is placed

in the planning process at the beginning of the layout development to ensure high quality layout

designs. The developed alternatives can take the form of a block layout which shows the relative

locations and sizes of the planning facilities (or departments) and/or a detailed layout which

shows the exact location of all equipment, work benches, and storage areas within each

department. The representation of the layout will either be discrete, which is where the facility

floor is divided into equally-sized grids representing the locations of the departments (Figure

1.1a) or a continuous layout representation where the facility floor is not divided equally but is

represented as a continuous plane (Figure 1.1b).

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a: Discrete representation

b: Continuous representation

Figure 1.1: Discrete and continuous representation of the plant floor.

Realistically most facility areas are not equally-sized as it relates to an overall depiction of the

facility, which makes the continuous representation a more flexible adaptation to use when

modeling the layout problem. Because the departments are not located within equally-sized areas

in this study the layout will be represented continuously.

Input/Ouput (I/O) points indicate the entering and exiting locations for a machining cell.

Ho and Moodie (1997) discusses the importance of I/O locations when automated material

handling devices are in place to ensure and maintain efficiency of flow within the cell. I/O points

can be located either at the center of the cell (the centroid of the cell) or along the cell’s

boundary due to the variance in the size and overall shape of the cell (Xiao et al., 2013). Xiao et

al. (2013) also states, that when the I/O points of the cell are not located at the center but along

the boundary of the cell the total travelling distance (TTD) is affected. Many studies present

cases in which the fixed location of the I/O point is at the center of the cell. However, in this

paper I/O points are considered and can be located anywhere within a department or along the

boundary of a department.

3

The orientation of the department is a major component in the calculation of the distance

a part travels as well as the effect the I/O point has on the cost calculation, as mentioned above.

The orientation of a department can be either fixed or may be allowed to vary. A department is

said to have vertical orientation if the longer side of the cell is along the y-axis and horizontal if

the opposite is true. A department with fixed orientation is most commonly considered in

situations where the plant floor may be restricted in size, or the location to which the cell will be

assigned has other items that have already been placed or have existed in the space (i.e. large

machinery that may be too costly to move or re-locate). This paper will consider variable

orientation due to the amount of floor space available within each department.

The FLP can be categorized as either static or dynamic. In the static FLP (SFLP) the

material flows are assumed to be constant during the planning horizon. However, in the dynamic

FLP (DFLP) there are multiple periods in the planning horizon, and the flow of materials

changes from period to period. The objective then becomes to minimize the sum of the material

handling cost for each period and the rearrangement costs. Rearrangement cost is the cost of

rearranging the location of a department between consectutive periods. In this paper, the SFLP is

considered.

There are four basic types of FLPs (Tompkins et al., 2003) :

1) Product layout or otherwise known as a flowshop environment includes a combination of

workstations performing operations on similar products or components (i.e.

production/assembly line).

2) Process layout or a job shop environment consisting of a group of departments that

perform similar processes on a large variety of products. The machines are group based

on machine type based on the sequence of operations (i.e. metal cutting and gear cutting

departments).

3) Product family or a group technology department which consists of a group of cells of

the same or similar processes performing operations on a family of products. Group

technology layouts are integrated with practices such as just in time (JIT), total quality

management (TQM) and lean manufacturing concepts and techniques. Another aspect of

this particular layout is known as cellular manufacturing (CM) where manufacturing

cells can be formed in a variety of ways. The most popular grouping technique involves

the grouping of machines to produce a family of parts. Once the groups are formed,

4

layout strategies will depend on the intra-cell layout which refers to the layout of the

machines within the cells and the inter-cell layout which signifies the layout of the cells

on the plant floor.

4) A fixed materials location layout is one where all of the work the product requires is

located at the site of production. An example of this would include large items such as

aircrafts and large sea vessels that are not easily moved (or moved at all) to manufacture.

The main attributing characteristic for the proposed FLP relates to problem three (3) above,

product family or group technology. This study focuses on the layout of three departments all of

which are named and “grouped” according the to “family” of products in that particular area.

Each cell performs a very similar set of processes on the part specifically moved through each

cell. Instead of focusing on the intra-cell layout, this paper considers the inter-cell layout

problem, which assigns the cells to locations on the plant floor.

This study will investigate the re-layout (or relocation) of already identified machining

cells within three departments, where the continuous representation is used to represent the plant

floor. The objective of this problem is to find the most efficient layout that will make the most

use of the made-available floor space while considering safety concerns for the walk-ways and

travelling paths used by production team members as well as paths of flow for part conveyence.

1.2 Problem Definition

Plant re-layout can be an expensive endeavor to explore. Modelling and solving the

problem mathematically will provide “good” (and perhaps optimal) feasible solutions based on a

given set of constraints that will allow the decision makers to view and analyze those solutions to

see which is more adaptable to a specific plant and its needs. As a result, the goal of this project

is to provide TMMWV layout proposals for the machining area, of which includes only the

machinery for model type A. Of the provided proposals, an optimal or “ideal” layout as well as

practical layouts will be pursued, with the objective of minimizing material handling cost while

considering safety issues. A major component to the success and continually improving

characteristic Toyota displays in its manufacturing practices is the attention and concerns for

team members and their safety.

5

1.3 Research Objectives

The objective of this study is to develop a mathematical model that will produce layout

alternatives in regards to floor requirements, capacity constraints, material handling costs and

team member safety. The anticipated results would serve as an ideal (optimal) layout as a basis

for future work or plant expansions. Ideally the research methodology, which will be discussed

in the sections to follow, will constitute an improved process for times to follow.

1.4 Organization

The organization of this problem report is as follows: Chapter 2 comprises a brief

literature review on the FLP and its problems, methodologies and a case study for layout designs

for cellular manufacturing. Chapter 3 presents the problem statement in its entirety, which will

include current plant diagrams, and the methodology used for solving the problem. Chapter 4

will conclude the report with a discussion of the achieved results from the problem, conclusive

remarks and recommendations for future work.

6

CHAPTER 2: BRIEF LITERATURE REVIEW

2.1 Literature Review

Bazargan-Lari (1997) presented the application of multi-objective inter- and intra-cell

layout designs methodologies in a cellular manufacturing environment of a dynamic food

manufacturing and a packaging facility located in Australia. The developed model, includes

constraints that address machine orientation, overlapping, floor boundaries, closeness

relationships, location preferences/restrictions, traveling cost (referred to as material handling

costs) all of which renders a more-realistic model consistent with the needs and requirements of

that particular space. The multi-objective approach includes a mathematical model, specifically a

mixed integer linear programming (MILP) model in conjunction with a combination of goal

programming and simulated annealing to generate efficient layout designs.

McKendall and Hakobyan (2010) presented a MILP model to solve the unequal-area

dynamic FLP (DFLP). There are three stages in determining the solution technique for the

DFLP: the first is the selection procedure which is to use the flow to determine the order in

which departments are to be selected for placement on the plant floor; the second is to use the

placement procedure to place departments on the plant floor which yields a layout plan and its

associated cost; and the third is the use of the tabu search to improve the layout plan obtained in

the second stage. The results demonstrated the finding of solutions quickly using the construction

technique (i.e. boundary search heuristic (BSH) which consisted of a selection and placement

procedure) and the tabu search, an improvement heuristic, uses BSH to generate layout plans

which performed well for solving large problems.

Heragu and Kusiak (1988) examines the machine layout problem in flexible

manufacturing systems (FMSs). The suggested method of solving the machine layout problem is

the use of one of two construction algorithms with the second algorithm known as the Triangle

Assignment Algorithm (TAA), known for its following advantages: low CPU time requirements

compared to existing algorithms; no initial solution required; and the required CPU time is fairly

equal for problems with equal and unequal machine sizes.

Xiao et al. (2013) presented a MILP model and a two-step heuristic method to solve an

unequal-area FLP with fix shapes, horizontal and vertical department orientations, and

input/output points. However, the authors restrict the I/O points to specific locations on the

boundaries of the department.

7

The survey presented by Drira et al., (2007) presents a frame-work to more effectively

navigate the research of facility layout literature and presentations based on the given facility

specifics such as workshop characteristics (i.e. product flow type, facility shapes and dimensions,

product variety and volume, material handling systems, multi-floor layout, flow-line layouts such

as backtracking and bypassing, and pick-up and drop-off location points), static/dynamic

considerations, continuous/discrete representation, problem formulation and resolution approach.

The conclusion of the paper offers several identified and discussed research directions congruent

with the focus and aim of the performed research characteristics needed for the defined study.

Other review papers available in the literature are Meller and Gau (1996) and Heragu and Kusiak

(1987).

8

Department 2 Department 1 Department 3

CHAPTER 3: PROBLEM STATEMENT AND METHODOLOGY

3.1 Problem Statement

The area of interest (the machining area) has 3 departments. In Figure 3.1 the continuous

representations of the department areas are depicted on the plant floor which shows the available

area (e.g. existing location of machines) and the unavailable area. The current layout has a

combination of 2 different machine types used for the machining of the existing models, the

model type A and the model type B. For the newer model, only the A machines are needed and

will be used thus requiring the removal of the model type B machinery. The problem consists of

the re-layout of the machining cells within each department. The problem is defined as an

unequal-area facility layout problem (FLP) which considers the continuous representation of the

plant floor.

Figure 3.1: The 3 machining departments of the transmission plant which requires re-layout.

The machining cells, part washers, inspection stations used for quality control and raw

material areas will be relocated in their entirety on the plant floor in a manner that reduces total

distance materials travel while considering worker safety such as safe traveling and walking

paths or aisles, as well as part conveyance routes throughout the machining area. See figures 3.2,

3.3, and 3.4 for the current layout of departments 1, 2 and 3, respectively, after removing the

type B machinery.

9

The assumptions for the FLP are as follows:

1. The layout within each cell (i.e. intra-cell layout) is given. It is important to note, team

member safety was regarded when the machining cells were installed in their current

location (during intra-cell layout design). It is standard that all machines are placed at a

certain distance apart from one another to ensure ease of accessibility for tasks such as

tool changes and machine maintenance.

2. In department 1, there were two identified machines that will be removed and replaced by

one machine that will be common to both parts of the model being machined in this

department.

3. All sections of the conveyors entering and leaving each cell will remain and be relocated

with that cell in its entirety.

4. In department 1 (see figure 3.2), the raw material (RM) staging area (identified

specifically in figure as cell 1) will be identified as its own “cell” feeding directly into

department 1. Also, cells 7 and 8 are dummy cells (unavailable space) and are fixed to

those locations on the plant floor.

Figure 3.2: The layout of department 1.

10

5. In department 2 (see figure 3.3), the staging area (identified specifically in figure below

as cell 9) will be identified as its own “cell” feeding directly into department 2.

Figure 3.3: The layout of department 2.

13 12

11

10

9

14

11

6. In department 3 (see figure 3.4), the staging area (identified specifically in figure below

as cell 15) will be identified as its own “cell” feeding directly into department 3.

Figure 3.4: The layout of department 3.

19 18 20

16

17

15

21

12

3.2 Methodology

An optimal layout for each of the three machining departments was first generated using

a mixed integer linear programming (MILP) model. The model requires specific inputs (e.g. cell

dimensions) that were taken from the layout provided by the plant. Each machining cell that

received or dispersed part flow was given an identifying cell number (i.e. the part washer,

inspection stations used for quality control, raw material cells, etc.) as depicted in the above

Figures 3.2, 3.3 and 3.4 in Section 3.1.

Next, the indices, parameters, and decision variables are defined for the MILP model.

Indexes:

i, j = 1,…, N where N is the number of cells within the machining area.

Parameters:

��,� Material flow quantity from cell i to cell j

��� Lower (minimum) length of cell i allowed for orientation

�𝑈� Upper (maximum) length of cell i allowed for orientation

𝑊�� Lower (minimum) width of cell i allowed for orientation

𝑊𝑈� Upper (maximum) width of cell i allowed for orientation

��� Lower (minimum) perimeter of cell i allowed for orientation

�𝑈� Upper (maximum) perimeter of cell i allowed for orientation

𝐵� Length of layout area on plant floor

𝐵� Width of layout area on plant floor

� A large number

Variables: (��, ��) The centroid of cell i

(�1�, �1�) Location of the lower left corner of cell i (�2�, �2�) Location of the upper right corner of cell i (𝐼��, 𝐼��) Location of the input point of cell i (���, ���) Location of the output point of cell i

���,� Horizontal distance from the output point of cell i to the input point of cell j

���,� Vertical distance from the output point of cell i to the input point of cell j 1 if cell � is to the left of cell �

(���,� ) { 0 ��ℎ������ 1 if cell � is to the north of cell �

(���,�) { 0 ��ℎ������

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Next, a nonlinear mathematical programming formulation is presented below to solve the

proposed FLP given the data set for each department.

Minimize z = ∑𝑁 ∑𝑁 ��,� ( �� + �� )

�=1 �=1 �,� �,�

(3.1)

Subject to:

��� ≤ (�2� − �1�) ≤ �𝑈� i (3.2)

𝑊�� ≤ (�2� − �1�) ≤ 𝑊𝑈� i (3.3)

��� ≤ 2(�2� − �1� + �2� − �1�) ≤ �𝑈� i (3.4)

�1� ≤ �2� ≤ 𝐵� i (3.5)

�1� ≤ �2� ≤ 𝐵� i (3.6)

�� = 0.5�1� + 0.5�2� i (3.7)

�� = 0.5�1� + 0.5�2� i (3.8)

�2� ≤ �1� + �(1 − ���,�) i and j, i ≠ j (3.9)

�2� ≤ �1� + �(1 − ���,�) i and j, i ≠ j (3.10)

���,� + ���,� + ���,� + ���,� ≥ 1 i and j, i < j (3.11)

���,� = |��� − 𝐼��| i and j, i ≠ j (3.12)

���,� = |��� − 𝐼��| i and j, i ≠ j (3.13)

��, ��, �1�, �2�, �1�, �2� , 𝐼��, 𝐼��, ���, ��� ≥ 0 i (3.14)

���,�, ���,� ≥ 0 i and j, i ≠ j (3.15)

���,�, ���,� = 0 �� 1 i and j, i ≠ j (3.16)

The objective function (3.1) is used to minimize the total traveling distance (TTD).

Constraints (3.2) – (3.4) ensure that each cell is within its the length, width and perimeter. Very

similar to these, constraints (3.5) and (3.6) ensure that the lower left and upper right coordinates

of each cell is within the boundary of the layout area on the plant floor considering horizontal

and vertical orientation. Constraints (3.7) and (3.8) are equations to find the centroid location of

each cell. Constraint sets (3.9) and (3.10) gives the relative locations between pairs of cells (e.g.

cell 1 is to the left of cell 2). Constraint (3.11) makes certain that no two departments overlap.

Constraints (3.12) and (3.13) gives the rectilinear distance from the output of cell i to the input of

cell j. The final constraints, (3.14) – (3.16), denote the restrictions on the variables.

14

CPLEX, an optimization software package, is a solver that has the ability to solve a linear

mathematical programming model of a problem and return the optimal solution. A modeling

language is used to generate the model for the CPLEX Solver. The model must be written into

the modeling system, MPL (Mathematical Programming Language) with only linearized terms.

To linearize the model, the standard method is used to linearize constraints (3.12) and (3.13).

Due to this change, the terms in the objective function (3.1) must be rewritten as well and be

replaced with the following. 𝑁 𝑁 + − + −

�������� � = ∑�=1 ∑�=1 ��,� (���,� + ���,� + ���,� + ���,� )

(3.20)

As a result, the MILP model consist of objective function (3.20) subject to constraints (3.2) –

(3.11), (3.14), and (3.16) – (3.19).

��� − 𝐼�� = ��+ − ��− i and j, i ≠ j

�,� �,� (3.17)

��� − 𝐼�� = ��+ − ��− i and j, i ≠ j

�,� �,� (3.18)

��+ , ��− , ��+ , ��− ≥ 0 i

�,� �,� �,� �,� (3.19)

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3.3 Data

The data defined in Section 3.2, was collected using measurement tools within the

AutoCad software from the provided detailed layout of the current design. Table 4.1 below is an

overview of the data lifted from the AutoCad drawing and used for the MILP model discussed in

Section 3.2.

Table 3.1: Summary of data collected for problem.

0

W idth Le ft.

ngth Perimeter ft. ft.

C1 Raw Material 5 25 60 C2 Cell 1 30 110 280

C3 Cell 2 35 75 220

C4 Cell 3 35 75 220

C5 Cell 4 20 40 120

C6 Cell 5 20 5 50

C7 FIXED 200 65 530

C8 FIXED 50 125 350

DEPARTMENT 1 325 190 920

C9 Cell 1 20 55 150

C10 Cell 2 35 95 260

C11 Cell 3 25 95 240

C12 Cell 4 15 25 80

C13 Cell 5 75 15 180

C14 FIXED 50 120 340

DEPARTMENT 2 325 120 780

C15 Cell 1 30 25 110

C16 Cell 2 15 120 270

C17 Cell 3 30 115 290

C18 Cell 4 15 30 90

C19 Cell 5 15 30 90

C20 Cell 6 10 5 30

C21 FIXED 120 60 360

DEPARTMENT 3 325 150 950

C22 Assembly FIXED 0 0

16

Production (part) flows (��,�) are needed to calculate the objective function value (OFV) in the above model discussed in section 3.2 (objective function (3.20)). The production plan for

the machining area was approximated at 600 parts per shift (3 shifts, 1800 parts/day) for all 3

departments. This amount was divided equally among the machining cells in its respective

department and the flow was surveyed according to the process flow from cell to cell (e.g. in

department 2, the machining cells are mirroring processes. The 600/shift part flow was divided

equally among the 2 cells to represent an accurate flow route). Table 3.2 shows the exact flow

from each cell in their respective departments.

Table 3.2: Flow matrix for machining cells in departments 1, 2, and 3.

17

The collected data entries and the proposed MILP model were used to optimally layout

the cells for all three departments as well as present layout alternatives to depict the machining

area in its entirety (i.e. present inter-cell layouts)., the fixed departments are identified as well, in

addition to assembly. Since the assembly area was not included in the layout area, this particular

department was designated as a single point at the very top of the layout area. From the current

plant layouts/designs provided, the production flow carries from the machining area and enters

the assembly area for the assembly of the full part. In order to adequately define the product

flows, and to evaluate the layout, an input/output point for the assembly area was defined and

utilized to identify a thorough product flow. However, the layout of the machining area

(departments 1, 2, and 3) and the assembly area should be considered simultaneously, since these

two areas interact with each other (i.e. materials flow between them), and the layout of one

affects the layout of the other.

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CHAPTER 4: COMPUTATIONAL RESULTS AND CONCLUSIONS

4.1 Data and Discussion

To graph everything in a relative location (relative to the plant floor), the I/O point of the

assembly area was located above the top right corner of department 1, above the top center of

department 2 and above the top left corner of department 3. Completing it this way would ensure

that when the entire floor was evaluated for layout alternatives, that the other designs achieved

would be as comparable as possible. Figures 4.1, 4.2 and 4.3 shown below are the optimal

layouts for departments 1, 2 and 3 based on the MILP model and the given data inputs.

Figure 4.1: Optimal layout generated by MPL/CPLEX for department 1.

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Figure 4.2: Optimal layout generated by MPL/CPLEX for department 2.

Figure 4.3: Optimal layout generated by MPL/CPLEX for department 3.

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The overall cost of the solution was calculated to be 145,500.00 feet. The solution means

that with this layout arrangement, the parts have to travel a total of 145,500 feet (TTD =

145,500). In Figure 4.4, you can see the entire floor layout for the machining area.

Figure 4.4: Overall layout of the machining area.

A second alternative overall layout was generated as well using MPL/CPLEX. The

difference being the I/O points were allowed to vary. The layout, figure 4.5 below, had a solution

of 55,500 feet, which is a 61.8% improvement over the layout obtained in Figure 4.4.

Figure 4.5: Alternative overall layout of the machining area

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4.2 Safety Considerations

Safety is a major priority to the environment and culture of the plant. With employing

over 1,300 team members in areas across the plant, safety and ergonomic studies have become

an important factor with how the plant makes its decisions especially regarding facility changes.

For simplicity purposes the safety outlook was summarized into two focal points regarding how

to produce the best design alternatives possible for both production and the team members. The

first being the traveling paths for team member safety. It is a company standard that any traveling

path throughout the plant, especially in a heavy industrialized area, must maintain at lea

st a 10-foot-wide identified pathway to ensure that team members are easily seen and can

maneuver if necessary. This becomes essentially important when walking between the machining

lines (or cells) and doing their daily required tasks. Notice the block layouts are given in figures

4.4 and 4.5 for the machining area. The next step would be to obtain a detailed layout, where

aisle widths for team member travel would be obtained.

In addition, consideration for the material handling path to the machines required by the

part conveyance team in this area is particularly important as well. Just like the standard above

for travelling paths, the plant requires a certain amount of space to and from each cell for part

delivery for the safety of the workers in that area. This consideration is targeted directly for the

raw material cells located in each department. Because of the automated feature of the cells (i.e.

the material handling section for departments 2 and 3) it is important to ensure that the

conveyance team has a certain amount of clearance and accessibility to deliver to the raw

material cells since there is a level of interaction with these automated systems. In department 1,

the raw material zone is actual a manual zone where team members use fork “tuggers” to deliver

to the cell and to collect what they need during production.

4.3 Conclusive Remarks and Future Research

The results obtained serves as an excellent starting point for further layout developments.

As discussed above, the safety considerations are an important aspect to any industrial company

who places employee safety at the top of the priority list. The most common practice used is to

solve the problem in two steps; the first being to obtain a block layout showing the sizes and the

relative locations of the cells; the second step is to obtain a layout design showing the specific

details of the layout such as aisle widths, specific locations of machines within the cells, etc. (i.e.

22

detailed layout). This sort of problem takes a considerable amount of time to solve and evaluate.

It is the suggestion of this study to pursue and set this option in place for future work. Another

goal for future research is to consider the layout of the machining and the assembly area

simultaneously because of the high interaction between the machining and assembly areas.

23

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