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PROJECT TOPIC: APPLICATION OF MODELS IN INVENTORY MANAGEMENT IN OIL AND GAS COMPANIES
Department: Engineering management
AMOUNT: 20,000
FORMAT: MS WORD
PAGES: 101
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Abstract Preview
This research applied models in inventory management in oil and gas companies utilizing the distribution center at in Oil and Gas Organization as a contextual investigation for information assortment. The review distinguished the materials/parts oversaw, not set in stone and applied inventory models utilized in the management of loaded things/unrefined substances and limited inventory investment to boost benefit. The Strategy for Request of Inclination by Likenesses to Ideal Arrangement (TOPSIS), Pareto investigation and Scientific Pecking order Cycle (AHP) models in inventory management were applied. AHP model first concern with pressure measure things, trailed by Control Framework and the least was fulfillment. Results got utilizing TOPSIS and Pareto investigation had all the earmarks of being comparable, which set which put the control systems as the most significant with the most elevated use rate, trailed by pressure measure. Subsequently, the best two need things for inventory management of oil and gas companies were pressure measure things and control systems. In light of the discoveries, the TOPSIS model showed up as the ideal and the most actually suitable model for inventory management in the oil and gas industry.
TABLE OF CONTENTS
Title Page i
Declaration ii
Certification iii
Dedication iv
Acknowledgement v
Abstract vi
Table of Content vii
List of Figures ix
List of Tables x
1.1.1 Characteristics of Inventory Management 4
1.2 Statement of Problem 6
1.4 Significance of the Study 7
CHAPTER TWO: LITERATURE REVIEW 9
2.1 Theoretical / Conceptual Framework 9
2.1.1 Theory of Constraint 9
2.1.2 Lean Theory 10
2.1.3 Stochastic Inventory Theory 10
2.2 Empirical Review 11
2.2.1 The Oil Industry 13
2.2.2 Inventory 14
2.2.3 Inventory Management 20
2.2.4 Inventory Management Models 22
2.2.5 Application of Inventory Management Models 27
2.2.6 Challenge in Implementation of Inventory Mgt. Technical 32
2.2.7 Symptoms of Poor Inventory Management 34
2.2.8 Inventory Management Improvement 35
2.2.9 Summary and Knowledge Gap 37
CHAPTER THREE: MATERIALS AND METHODS 39
3.1.1 Study Area 39
3.1.2 Inventory Models Description 39
3.1.3 Material Stock Inventory 39
3.2 Method 39
3.5 Method of Data Analysis 49
CHAPTER FOUR: RESULTS AND DISCUSSIONS 50
4.1 Results 50
CHAPTER FIVE: SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 65
5.4 Contribution to Knowledge 67
Page
Figure 1.1: Types of demand classification 6
Figure 3.1: TOPSIS Algorithm 46
Figure 4.1: Pareto curve for the study 54
Figure 4.2: Priority of inventory / stock mgt. 54
Figure 4.3: TOPSIS Prioritization for inventory mgt. 55
Figure 4.4: Plot of AHP scores of the alternatives 55
Pages
Table 2.1: Knowledge Gap 37
Table 3.1: The Saaty (1980) Rating Scale 40
Table 3.2: Pairwise Comparison Matrix 42
Table 3.3: Weight of Pairwise Comparison Matrix 42
Table 3.4: Random Consistency Index 43
Table 4.1: Pareto scores of the categories 49
Table 4.2: Assigned weights to criteria 49
Table 4.3: xij = Score of option i with respect to criterion j 49
Table 4.4: The normalized decision matrix 50
Table 4.5: The weighted standardized decision matrix 50
Table 4.6: Computation and result of relative closeness to the ideal solution 50
Table 4.7: TOPSIS options weight 51
Table 4.8: Scores of alternatives “A” with respect to criterion “C” 51
Table 4.9: Pairwise comparison matrix 51
Table 4.10: Normalized Pairwise comparison matrix 51
Table 4.11: Criteria weight computation 52
Table 4.12: Consistency computation 52
Table 4.13: Weighted sum computation 52
Table 4.14: Ratio of weighted sum value to criteria weights 52
Table 4.15: Validated criteria weight 52
Table 4.16: Normalized value for the score of alternative wrt to criteria 53
Table 4.17: Model synthesis 53
Table 4.18: Overall priorities for inventory mgt using analysis 53
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