Numerical example

The analysis begins w ith a numerical example for the MOVE and OVE metrics based on the theory previously discussed in Section 6.3 and 6.4.

First, the evaluation o f the OVE and MOVE m etric’s effectiveness percentage is demonstrated based on a simple example involving 2 retailers. The distance between each retailer and the base point and retailers’ weight requirement is based on the layout shown in Figure 6.6. Here, the distance between each point is assumed to be symmetric, that is, the total distance is similar for both directions and the unit used for weight o f the product is in kilograms (kg). The calculation is determined based on sample input data shown in Table 6.1.

Retailer A

A ^ ! 70kg)

10 km

10km

14.14 km

base Retailer B

(210 kg) Figure 6.6: R etailers’ layout and weight requirement

Table 6.1 Input data for the perform ance measurement calculation

Input Data

1 Maximum transportation capacity 400 kg

2 Actual journey time 70 min

3 Maximum Speed 1 km/min

4 Quality 95 %

5 Break time 15 min

6 Excess Loading time 10 min

7 Unladen Vehicle weight 500 kg

8 Available travelling time 55 min

In this case, two possible routes exist to make the replenishment and will be examined using both metrics. The vehicle has an option to choose either to replenish retailer A first followed by retailer B, or the other way around. By only considering the distance factor to determine the optimal route for symmetric cases, it seems that either routes can be chosen when m inim ising the distance travelled. However, the vehicle energy consumed for each route is different. This is because the load carried by the vehicle varies according to the retailers’ requirements. Therefore, it is more accurate to

determine an efficient route by considering both distance travelled and vehicle load optimal route, with the least distance (km) and energy consumption (kg-km).

Table 6.2: The distance and weight-distance calculation for route 1 and route 2

Route 1 the utilisation and tim e efficiency values for the MOVE metric are shown in Table 6.4.

Table 6.3 : OVE availability and speed rate calculation

Factor Calculation

Availability

Planned weight distance 400 kg *1 km/min * 55 min = 22000 kg-km Lost weight distance 400 kg *1 km/min *10 min = 4000 kg-km Actual weight distance (22000-4000) kg-km = 18000 kg-km

.•. Availability 18000 kg-km _ gn0/^

22000 kg-km

Speed rate

Actual travelling time 55 min-10 min = 45 min Average speed rate 34.14 km .

--- = 0.76 km/min 45 min

.‘. Speed rate 0.76 km/min 1 km/min 76%

Table 6.4 : MOVE vehicle utilisation and time efficiency calculation

Factor Calculation

Shortest possible time (34.14 + 15) min = 49.14 min .‘.Time efficiency 49' 14m in=70.2%

Hence, the performance rate for the OVE metric for both routes is:

i) Route l ’s perform ance rate = 32.8% * 76% = 24.93%

ii) Route 2 ’s perform ance rate = 39.3% * 76% = 29.87%

The route efficiency for the M OVE metric for both routes is:

i) Route efficiency for route 1 2 2 9 7 0 k g -k m

= = 100%

22970 kg - km

ii) Route efficiency for route 2 , 22970 kg - km

241 4 3.2 k g -k m

Finally, the total OVE percentage is determined by multiplying the availability rate percentage with the perform ance rate and quality rate percentages as shown in Table 6.5. The MOVE values for both routes are also shown in Table 6.5.

Table 6.5 : OVE and M OVE values for route 1 and route 2

Route 1 Route 2

MOVE 26.82%* 100% *70.2%*95% = 17.89% 26.82% *95.14%*70.2% *95% = 17.02%

OVE 82% *24.93%*95% = 19.42% 82%*29.87%*95% = 23.27%

A contrast can be seen betw een the OVE and M OVE results in Table 6.5. Route 2 has a higher performance than route 1 using the OVE metric, but with the MOVE metric, route 1 is superior to route 2. From Table 6.5, it can be seen that the OVE metric is driven by the perform ance rate, 24.93% for route 1 and 29.87% for route 2. The capacity rate that contributes to the total OVE performance rate percentage is higher in the case where the vehicle has a higher weight-distance value for the trip. This suggests that the OVE m etric gives more priority to heavy loads carried along longer distances since the capacity rate value is the total weight-distance divided by the actual weight-distance value. However, as has been discussed before, increasing the vehicle’s weight will cause an increase in the fuel consumption. As a result, such increase may influence the vehicle operating cost and also the maintenance cost.

Further, the M OVE m etric produces a higher vehicle effectiveness for route 1. Table 6.5 shows that route 2 contributes to a lower route efficiency percentage since the

total weight-distance for an actual route taken is longer than the optimal, minimised weight-distance. Therefore, the MOVE metric is capable o f identifying the best route that minimises the energy consumed by the vehicle. Moreover, the vehicle utilisation rate in the MOVE calculation points to the most suitable size o f the vehicle to be used in order to better utilise resources and reduce wasteful activities. The vehicle utilisation rate will decrease as the vehicle size increases or as the size o f the vehicle loads decrease. Figure 6.7 illustrates the effect o f different maximum transportation capacities on vehicle utilisation rate and overall MOVE percentage. The effect of vehicle utilisation on the vehicle load factor will be discussed later in Section 6.7.

20 18 16 14 12 ^_

£

10 w 8 So 6

4 2

0

400 800 1200 1600 2000

M axim u m transportation capacity

Figure 6.7: The effect o f d ifferen t m axim um tran sp o rtatio n capacity on vehicle utilisation ra te and M O V E percentage

As can be seen in Figure 6.7, the vehicle utilisation rate and total vehicle performance decreases to almost h alf o f the current rate by doubling the vehicle size capacity to 800 kg. The percentage is decreased further as we increase the vehicle capacity. Thus, the decrement o f vehicle utilisation rate and MOVE percentage decrement is inversely proportional to the increment o f maximum transportation capacity. It is suspected that the same condition also holds for the vehicle capacity rate in the OVE calculation

V e h ic le utilisation (% ) M O V E (% )

145

when different vehicle sizes are used for replenishment. A large vehicle capacity will decrease the capacity rate and this influences the performance rate and total OVE score.

Next, the OVE and M OVE metrics are evaluated when the requirement o f each retailer is changed by assigning the heaviest load to retailer A instead o f retailer B.

Interestingly, the new result shown in Table 6 . 6 is similar to that derived from the previous analysis. It is obvious here that route 2 produces higher weight-distance since the vehicle is carrying the total load from the base along the longer route between the base and retailer B. Furthermore, the vehicle is carrying the heavier load after making the replenishm ent to retailer B.

Table 6.6: MOVE and OVE results after weight requirement changes Route 1 Route 2

MOVE 8.9431 8.5085

OVE 9.7063 11.6071

The situation is different when retailer A requires small loads compared to retailer B.

This is because the M OVE metric will give higher performance for route 2 rather than route 1, as less energy is used by the vehicle to deliver the heavy loads first at retailer B, even though it is a longer distance from the base. Figure 6 . 8 illustrates the 4 MOVE factors for both routes in the situation where Retailer A only requires 70 kg compared to the requirem ent o f Retailer B o f 210 kg. Therefore, the decision as to which route to use for the trip is not dependent on either distance or weight factor only but on both factors.

r p "v — - § ■

So far, the OVE and MOVE metrics have been computed for equal distances between alternative routes. The analysis continues with the evaluation for 3 retailers where different total distances occur when a vehicle chooses a different sequence o f retailers during the trip. With a similar physical layout as in section 5.2, there are two possible replenishment sequences for each route are as follows:

Route 1 :

Table 6.7 MOVE, OVE and KPI measurement for 6 routes

Metrics Factors Route 1 Route 2 Route 3 Route 4 Route 5 Route 6

Vehicle utilisation (%) 32.47

MOVE Route efficiency (%) 99.39 83.2 81.71 82 82 100

Time efficiency (%) 78.57

Quality (%) 95

MOVE (%) 24.09 20.16 19.8 19.87 19.87 24 24

Availability (%) 82

OVE Speed (%) 89

Capacity rate (%) 40.3 47.4 49.6 49.2 46.9 39.7

Performance (%) 35.87 42.19 44.14 43.79 41.74 35.33

OVE (%) 27.94 32.87 34.39 34.11 32.52 27.52

KPI’S Distance (km) 48.28 48.28 48.28 48.28

W eight-distance (kg-km)

with unladen vehicle 32700 39061.6 39776.2 39634.8 38920.2

IHB

The routes that give highest performance for all metrics are highlighted in the Table 6.7. It can be seen that route 6 is the best route using the MOVE metric, whilst the OVE metric allocates the highest performance to route 3. The optimal route determined by the M OVE metric is based on the minimum distance travelled and weight-distance carried by the vehicle. Using the OVE metric, routes having higher distances tend to contribute to a high weight-distance value to maximise vehicle performance.

Hence, the examples show that the M OVE metric outperforms the OVE metric as it minimises the vehicle distance travelled and energy consumed. The impact o f the MOVE and OVE metrics and TSP approach in terms o f cost will be discussed in the Section 6.8.