Optimizing Supply Chain Efficiency For DHL Through Go Green Initiative

Demonstrate that you can effectively analyse business decision problems, apply mathematical modelling approaches such as Linear Programming or Integer Programming to solve the problems. You must master Excel “Add In” features such as Solver to obtain the optimal solutions, generate a sensitivity analysis report, and suggest courses of action for management. 

Background

This study is based on a case study of DHL, a transport and logistics firm. The supply chain team has undertaken a mission to embrace the go green environmental protection program. In order to achieve this mission, the company has undertaken to improve the efficiency of carbon dioxide across the global operations by 30% compared to the 2013 baseline. The aim is to ensure that there is no excess or limited emission of carbon dioxide into the environment.

The supply chain team has undertaken to achieve the objective of go green initiative by re- evaluating the supply of their electronic products, specifically LCD TV sets (LCD23 and LCD 42 TV SETS). The major objective of this report is to help the supply team in determining the optimal number of LCD TV sets produced by different sub-contractors. The company had a total of seven sub-contractors each of which were expected to produce different number of LCD TV sets.

The company is further interested in determining the optimal means of transport that would support the go green initiative that they hand undertaken. The company had different transport means which they could use depending on the availability and efficiency. The transport modes available include regular air, air express, road, road LTL (less than truckload), road network, rail and water. Shipping times vary from 2 to 10 days depending on the distance and the mode of transport used.

Other cost that are anticipated in the transport of the TV sets are the government incentives and legislations to reduce emission of carbon dioxide into the atmosphere. Further, the team anticipated a rise in the brand value of the TV sets due to the increased awareness among the customers.

The major task of the team is to find out how the maximum potential reduction in the carbon dioxide emission could be made possible through a potential CNY 3.3 billion budget for manufacturing and shipping LCD TV sets from the ODMs and Dc. This objective has been achieved by establishing the maximum number of LCD TV sets from the ODMs and Dc.

Past restudies by the world economic forum discovered that there is a great amount of carbon dioxide gas emissions into the atmosphere. The studies further that a significant percentage of these emissions are resulting from the transport and logistics sector. This implies that transport and logistics firms have to really think of the best way possible to curb the possible effects and reduce the amount of carbon dioxide emissions into the environment.

Objective

 In fact, the summary of the study stated that “Significant movement is expected towards reduced supply chain carbon intensity. This will create both opportunities and risks for logistics and transport firms, with changes in supply and demand driven by regulation of carbon emissions, higher and more volatile fuel prices and evolving consumer demand. The sector can play an influential role in decarbonisation, both in its own operations and through broader supply chain optimization. This provides direct benefits through reduced costs, managed risks and business growth.” The study further recommended a switch in the mode of transport if possible to curb the continuous increase in emission of this gas into the environment.

There are other several literature that links transport with increased emission of carbon dioxide into the atmosphere. According to the study by (Alexander, Sergey, Mei, Ray, & Anvar, 2010), an increase in the accumulation of carbon dioxide and biomass is linearly related to transportation. The study demonstrates that several transport means emits certain amounts of carbon dioxide into the atmosphere. This study however did not specify whether there are certain transport means that could be considered as safe and could be encouraged. The study, however, gave a recommendation of conducting a further study to find out the extent of the effects of these emissions in the environment.

A study by (Zhang, Qiao, Cao, Jing, & Zhong, June, 2014) reveals that the rise in carbon dioxide will increases the rate of plant growth only up to a certain level. The study reveals that although carbon dioxide is a vital gas for plants growth, it is only needed up to a certain level beyond which it becomes toxic. The study, however, has not revealed the optimal level beyond which carbon dioxide become toxic. There is a recommendation for a further scientific research to find out the current level of carbon dioxide the actual optimal level beyond which the emissions become toxic. The study also links heavy emissions of carbon dioxide into the atmosphere to transport sector.

Increased emission of carbon dioxide causes global warming. A study by (John, Janruary, 2013) reveals that there is an increased level of global warming as a result of a continuous emission of carbon dioxide into the atmosphere. The study recommended that there is a need to revise the various transport means including limiting the use of certain means in order to reduce emission of these gases. While the study suggested elimination of certain transport means as a measure to reduce carbon dioxide emission into the atmosphere, the study did not specify some of the most dangerous means that should be specifically avoided.

Transport Means

Continuous emission of carbon dioxide into the atmosphere causes a change in the global climate. This change in global climate a disaster that could cause several effects to both plants and animals including human beings as well. A study by (Guest, January, 2010). The study reveals that climate change affects all aspect of human life including agriculture which is the most important sector of the economy. The study, however, did not identify the dangerous sources of carbon dioxide that could be easily avoided.

Carbon dioxide causes a great threat to the fishing industry. A study by (Sun, et al., December, 2014) reveals that carbon dioxide emissions is the most dangerous threat to aquatic life. This implies that fish will deficiency in their food if the emissions continue in a great extent. The study by (Wang, et al., March, 2016) further reveals that excess emission of carbon dioxide into the water may cause death of certain important water animals. The study by (Sun, et al., December, 2014) specifically identifies water transport as the major cause of excess carbon dioxide released into the water bodies. The study recommends a further research on how to reduce emissions of carbon dioxide gas into the water by closely monitoring the vessels used as a means of transport.

Excess release of carbon dioxide into the atmosphere may lead to unpredictability of rainfall and rainfall distributions. A study by (Yun, 2011) specifically identifies that excess release of carbon dioxide into the atmosphere may eventually lead to changes in amounts of precipitations and the distributions of precipitations that so occur. The study reveals that this is as a result of climate change. The study further reveals that one of the major causes climate change as a result of excess emission of carbon dioxide into the atmosphere is the uncontrolled means of transport. The study recommends a there need to be more insightful study done on the major transport means and a clear evaluation of the amounts of carbon that they emit into the environment. This is an argument that has been backed up by the study by (John, Janruary, 2013).

This section outlines the description of the mathematical approach used to solve the problem in this report. Since the problem at hand is an optimization problem, the method adopted for solving the problem is the optimization method by linear programming. Linear programming in this context refers the analysis done in order to enable one to be able to choose an optimal course of action in a case where the problem at hand exclusively contains linear functions for both the objective function and the constrains (Frankfort-Nachias, 2015).

Costs

A function in this context means a method of mapping one variable onto another (Lind, 2008). An objective function is a mathematical equation or equation that describes the objective of the problem (Stuart A., 2009). In our case, our objective is to minimize production cost of the LCD TV sets.

In this section, we display the results and the analysis of the results. The objective to find the optimal number of LCD TV sets (LCD 32 TV SETS and LCD 42) that will minimize the production of carbon dioxide by 30%.  Constrains used in this analysis are regular air, air express, road, road LTL and road- network. These variables have been named as X1, X2, X3, X4, X5 and X6 representing are regular air, air express, road, road LTL and road- network respectively. The decision variable is used as X1. A constraint is used in this case to mean a set of limitations or restrictions that determines the cost of production or transportation cost (Frankfort-Nachias, 2015).

The outputs have been produced using the excel Add- INS (solver). From the analysis results below, it is clear that the amount of LCD 32 TV SETS and LCD 42 TV SETS that is required in order to minimize production cost and reduce emission of carbon by 30% are 400000 for LCD 32 TV sets.

Similarly, the required constraints amounts are 1174 units, 468832 units, 51571 units, 3223 units, 2637 units and 2578 units for are regular air, air express, road, road LTL and road- network. Respectively.

Variable Cells
			Final	Reduced
	Cell	Name	Value	Gradient
	$D$14	Decision  variable X1	1407.408	1174.992
	$E$14	Decision  avriable X2	56156.8	46883.2
	$F$14	Decision  avriable X3	61772.48	51571.52
	$G$14	Decision  avriable X4	3860.78	3223.22
	$H$14	Decision  avriable X5	3158.82	2637.18
	$I$14	Decision  avriable 66	3088.624	2578.576

Constraints
			Final	Lagrange
	Cell	Name	Value	Multiplier
	$J$19	Units Produced LCD 32 TV SETS	400000	0
	$J$20	Units Produced LCD 42 TV SETS	600000	0

The extent of the reduction in CO₂ emission if the budget were increased by 10 per cent to CNY 3.3 billion. 

Given an increase an increase in the budget by 10 percent, we can still find the optimal amounts that needs to be produced.  In this section, we display the results and the analysis of the results. The objective to find the optimal number of LCD TV sets (LCD 32 TV SETS and LCD 42) that will minimize the production of carbon dioxide by 30%.

Constrains used in this analysis are regular air, air express, road, road LTL and road- network. These variables have been named as X1, X2, X3, X4, X5 and X6 representing are regular air, air express, road, road LTL and road- network respectively. The decision variable is used as X1. A constraint is used in this case to mean a set of limitations or restrictions that determines the cost of production or transportation cost (Frankfort-Nachias, 2015).

Mathematical Approach

The outputs have been produced using the excel Add- INS (solver).

The output of the solver analysis is represented below. The respective quantities of the constraint variables are 1407 units, 56156 units, 61772 units, 3860 units, 3158 units and 3088 units for regular air, air express, road, road LTL and road- network.

Cell	Name	Original Value	Final Value	Integer
$D$14	Decision  avriable X1	0	1407.408	Contin
$E$14	Decision  avriable X2	0	56156.8	Contin
$F$14	Decision  avriable X3	0	61772.48	Contin
$G$14	Decision  avriable X4	0	3860.78	Contin
$H$14	Decision  avriable X5	0	3158.82	Contin
$I$14	Decision  avriable 66	0	3088.624	Contin

The table below outlines the effects on the number of LCD 42 TV sets and LCD 32 TV sets given a 30% increase in the budget. It also outlines the effects on the carbon dioxide emission into the atmosphere. From the output below, it clear that the volume of production of LCD 32 TV sets units will change by 22 while the volume of production of LCD 42 TV sets units will change by 2711. This will ensure that there is an optimal production by DHL.

Cell	Name	Cell Value	Formula	Status	Slack
$J$19	Units Produced LCD 32 TV SETS	0	$J$19<=22	Not Binding	22
$J$20	Units Produced LCD 42 TV SETS	0	$J$20>=-2711	Not Binding	2711

Discussions and Conclusions

In this section, the focus is on some interesting observations and findings we can gather from the above analysis?  Similarly, we discuss some of the important aspects we can conclude about these findings?

The decision variable is used as X1. A constraint is used in this case to mean a set of limitations or restrictions that determines the cost of production or transportation cost (Frankfort-Nachias, 2015). Similarly, the required constraints amounts are 1174 units, 468832 units, 51571 units, 3223 units, 2637 units and 2578 units for are regular air, air express, road, road LTL and road- network. Respectively.

The findings in this report implies that the DHL can use any of the six modes of transport, that is regular air, air express, road, road LTL and road- network. The optimal decision would remain on the amount of LCD 42 TV sets and LCD 32 TV sets that it procure in order to minimize the emission of carbon dioxide and maximize on the profit. From this report, it is recommended that DHL should procure more of LCD 42 TV sets than LCD 32 TV sets. 

References

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Frankfort-Nachias, C. &.-G. (2015). Social Statistics for a diverse society. Thousand Oaks, CA: Sage Publications.

Guest, R. (January, 2010). Global Demographic Change, Carbon Emissions, the Optimal Carbon Price and Carbon Abatement. Global Economy Journal, 19.

Lind, D. A. (2008). Statistical Techniques in Business & . Boston.: McGraw-Hill Irwin.

Settlement Structures and Carbon Emissions in Germany: The Effects of Social and Physical Concentration on Carbon Emissions in Rural and Urban Residential Areas. (Janruary, 2013). Environmental Policy , 17.

Stuart A., O. K. (2009). Kendall’s Advanced Theory of Statistics: Volume 2A- Classical Inference & the linear Model. 

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