Design of Mixed Truck System with Milk Run Pick Up And Single Hub Cross Docking Distribution-A Case Study

 

Shobha N S^1*, Dr. K N Subramanya²

¹Assistant Professor, Department of Industrial Engineering and Management, R V College of Engineering, Bengaluru – 560 059, Karnataka, India

²Principal and Professor, Department of Industrial Engineering and Management, R V College of Engineering, Bengaluru – 560 059, Karnataka, India

 

 

ABSTRACT:

Logistics is a fundamental component in any automotive industry. The study involves the delivery system that consists of milk run pick up with the single hub cross-docking system. It was identified that there is no direct shipment of goods from supplier to the customer; a company is experiencing lower service quality of the delivery system. After adapting third-party logistics partner also there is a lower delivery rate of products. This study develops a model for the mixed truck delivery system that allows both single hub cross-docking with milk run and direct shipment. A mathematical model was developed to determine the total transportation cost and shows the 12% cost saving achieved by providing flexibility in transportation by efficiently using services provided by third party logistics.

 

 

 

1.0 INTRODUCTION:

The  automobile industry isn't best one of the international's most vital monetary sectors with the aid of the use of sales; it also takes up a major position in phrases of wonderful expectancies, product variety and technique complexity pushed by globalization and increasing patron requirements, manufacturers are compelled to offer a large range of car models and options. The vast product range-precipitated complexity and the stress of difficult global competition make it hard to make sure efficient logistics. This is the cause why commercial computing plays a primary position

 

 

for the duration of the whole automotive delivery chain, from allocation and garage of uncooked substances and components to production and shipping to timely spare components procurement. logistics is the organized movement of substances and, in a few cases, individuals. logistics control is characterized as a commercial enterprise arranging shape for the management of fabric, control, statistics and capital streams. all merchandise moved are contained in packages and for that reason, the analysis of the physical logistics flows and the position of packaging is a totally important trouble for the definition and design of manufacturing procedures, development of layout and increase in groups performance.

 

Cross-docking is a practice in logistics of emptying substances from a drawing near truck or rail automobile and stacking these materials especially into outbound vans, trailers, or rail vehicles, with almost no stockpiling in between. as stock prices talk to one of the essential cost in an inventory network, move-docking will become a fascinating distinct choice for warehousing. day, is a material taking care of operation, in which gadgets move unexpectedly and straightforwardly from inbound vans (ITs) to outbound trucks (OTs), within the wake of being a turn or merged with confined stockpiling desires, usually no longer surpassing 24 hours. those sort of centers are for the maximum part applied as part of "hub and spoke" plans, where (de)consolidation of freight happens as on account of transshipment, with items conveyed to clients in truckloads. Fig 1 indicates the aggregate of milk run with move docking.

 

 

Fig 1: The combination of milk runs with cross docking

 

As an end result, the supply chain is hooked up directly from the factor of origin(supplier)to factor of sale, the commodity is moving quicker, the inventory expenses, dealing with prices, and working costs are decreased and customer's simply-in-time demands are higher matched.
Jayanth Jayaram [1] discussed on the important factors to be considered while predicting the firm’s performances. It gives information regarding the integration of information, third-party selection, relationship building. Third-party providers will build up a supply chain management to a higher extent.  Rohith Batnagar [2] provided information related to managing the inbound as well as outbound logistics of raw materials from suppliers to manufacturers. Aicha Aguezzoul [3] research on The Third Party Logistic Selection provides detail information of procedure to select the third party. This paper is mainly focused on the exploratory type and mainly on reason, benefits, and risk with the 3PL. It provides information related to 3PL performance. A comparison in terms of advantage and disadvantage. Modelling, planning and evaluating techniques are learned from this paper. Analysing the relationship between the 3PL and supply chain. Michelle L.F Cheong [4] research on Logistic Outsourcing And 3PL Challenges provides that the overall trend in logistics outsourcing in moving higher service providers. The extent of activity involves the number of business holders. It provides the layers of 3pl challenges that is material flow layer, information flow layer and relationship layer. This paper helps us to identify and select the best third-party logistics considering all the feasibility information provided by the providers. Sukachai Penpokai [5] research on a Mathematical model for combined outbound logistics and inbound logistic using milk run deliveries provides detailed information of managing the inbound and outbound logistics using milk run deliveries.

The cross-docking system reduces transportation cost and minimise inventory cost [6]. Increase in customer loyalty, shorter lead times, financial savings, vehicle movement are the benefits of cross docking [7][8]. There is huge opportunity for undertaking research studied on milk run system [9]. 

The vehicle directing issue (VRP) is first talked about by Dantzing and Ramser [10] on the truck dispatching issue (TDP). Customary VRP is centered on dispatching armada on execution the conveyance benefit given a solitary stop, benefit hubs and amounts required. The goal is to limit travel separation or conveyance cost. In the current years, a few genuine requirements have been considered to a customary vehicle directing issue, for example, the capacitated VRP, the multi-terminal VRP, the VRP with time windows, the get and conveyance VRP. Theeratham Meethet [11] research on Vehicle Routing in Milk Run Operation provides information regarding the mathematical formulation that helps in vehicle routing. The paper displays an advancement model also, a model PC application for taking care of the vehicle steering issue on a huge scale milk-run operation. The authors proposed branch-and-headed calculation for tackling this issue. The execution and adequacy of the calculation arrangement are contrasted with that of a common branch-and-bound calculation. Fabian Meier [12] discuss on A Versatile Heuristic Approach for Generalizes Hub Location gives information regarding hub location model. This paper shows the ease of use of center point area models intensely relies on upon a fitting demonstrating methodology for the economies of scale. Sensible center point area models oblige more complex transport expense structures than the customary a rebate. Chong Chuan Chen [13] have discussed on A Solution For Cross-Docking Operation, Planning and Control provide information on the cross-docking network. The paper presents innovative work chip away at cross docking arrangement in three angles: enhanced anticipating compartment gathering, bunching, sequencing and distributing compartments to docks; ongoing planning handles the elements of holder landings and real bed exchanges, and cross-docking coordination directs constant assignment task/sequencing and asset administration to manage dynamic changes. It incorporates three layers of modules arranging layer for compartment arriving, gathering and designation; booking layer for element occasion taking care of; and coordination layer for execution control and asset management.

The earlier works carried by researchers indicates the importance of outbound logistics in a traditional system. There is little work available on 3PL service providers in the Indian context and its tangible benefits. This has motivated the authors to take up studies on milk run and cross docking systems. The outcome of the literature review has been productive in terms of providing various opportunities in furthering the existing researchers.

 

2.0 OBJECTIVES OF STUDY:

There is no direct shipment of goods from supplier the customer. The company is experiencing lower service quality of the delivery system. After adapting third-party logistics partner, there is the lower delivery of products. Miscommunication of information regarding delivery of goods, is causing the organization to switch to the different mode of transport for the quicker delivery rate. Logistic transportation cost is also high, when there is an urgency of delivery of goods. Overall logistic cost is 50 lakh per month. In order to address the above issues, the objectives set for study includes: analyzing the outbound logistic between interplants and to provide suggestion on single hub cross-docking with the direct shipment.

 

3.0 METHODOLOGY:

Following is the methodology adopted in order to meet the objectives.

 

Step 1: Collection of weight and volume:

We collected weight and volume of the material transported from karnataka region to North India and Maharashtra region. Table 1 and Table 2 represent the weight and volume supplied to Plant 4 and Plant 5. Currently, the automobile industry is using four Third party logistic partners. The table also contains the logistic provider name and logistic charges per kg according to the mode of transportation. It also contains tonnage/day, so we can illustrate the truck efficiency and table also mentions the transit time in delivering the material from suppliers to customer destination, here customer is interplant (Plant 4and 5).

 

 

Table 1: Logistics data from Karnataka region to plant 4

 

Table 2: Logistics data from Karnataka region to plant 5

 

Step 2: Mapping of Interplants location:

The automobile industry has seven plants in India. Plant 1, Plant 2, Plant 3, and plant 7 are located in Karnataka. Plant 4 is in Pakistan, Punjab, Plant 5 is located in Maharashtra and Plant 6 in Uttar Pradesh.

An Outbound logistics operation of a 3PL company usually follows the process as depicted below. The flow of materials from the suppliers to the customers is routed through a warehouse. The collection and delivery follow a schedule as given by the customer. This group has four of its interplant in Karnataka region. They have outsourced the Third-party logistics providers to look after the inbound and outbound logistic of an organization. Fig 5 shows the outbound logistics from supplier to a customer (interplant 4and5). Third party providers receive the smaller loads from a supplier, as it is smaller part loads, components go through two warehouses and later get accumulated for the full truck where they consolidated the products according to the customer location. Traditional lead time is about 8-9 days from Karnataka to North India region and 4-5 days transit time for Karnataka to Maharashtra region.

 

Fig 2: The outbound logistic from supplier to customer (interplant 4 and 5)

Table 3: The cost incurred for 3PL

 

Step 3: Current Logistic cost:

Data was collected for 10 months from Apr’14 and January’15. Table 3 shows the cost incurred for 3PL.

 

It is concluded that the automobile industry is using multi 3PL providers and there is always a difficulty in maintaining the partners. Overall Logistic cost is also 50 lakh per month when combining all the four partners. In order to reduce the transportation cost and to effectively increase the frequency of delivery of materials to the customer location, we have studied milk run with single cross docking model. By this method, we can switch to one or two 3PL providers instead of 4 to 5 Third-party logistics providers.

 

Step 4: Model of proposed system:

In this study, a mathematical model is proposed that represents the cost calculation by using the milk run pick up and cross-docking distribution. Fig 3 depicts the model proposed for the milk run pick up with cross-dock distribution. It is assumed that homogeneous vehicles are used. It is also acknowledged that the required conveyance amount from any provider to any customer does not point the confinement of one vehicle.

Fig 3: The model proposed for milk run to pick up with cross-dock distribution

The objective of the firm is to minimize the total cost. A mixed mathematical model is formulated to solve the problem. The following Figure 4 is the details of the model.

 

 

Fig 4: Flow chart for the milk run to pick up

Cost Calculation for Transportation cost:

Variables:

xp is the number of the truck traveling on route p.

 

Parameters:

Cp is the operating cost of route p.

δip equal to one if commodities supplied by supplier i are transported by trucks traveling on route p, otherwise, equal to zero.N is the total number trucks available.

Sets:

P is the set of all possible routes, indexed by p.

I is the set of all suppliers, indexed by i.

 

Objective Function:

The Milk run vehicle routing model is formulated as follows:

Min ∑ p€P cp xp                                                            (1)

 

Constraints:

∑ p∈P δp xp ≥ 1 ∀i ∈ I                                    (2)

∑ p∈P xp ≤ N                                                   (3)

xp≥ 0 and integer ∀p ∈ P                               (4)

 

The objective function (Equation 1) minimizes the summation of total milk-run transportation costs, which depends on the unit operating cost, truck utilization, and the trip distance. Constraints (2) ensure that all supplies demanded are satisfied by a milk-run trip. The number of trucks used is controlled by Constraints (3). Constraints (4) ensure that only positive whole numbers of trucks are selected.

 

Numerical Example:

The following example demonstrates the applicability of the model for interplants in Karnataka region and using the data derived from actual milk-run transportation network used in an auto industry.

No of vehicle used for milk run = 2;

No of suppliers = 4;

Routing = 2-1-3-7;

Total weight available per day from all four suppliers = 9 tons;

Total cost per truck for full truck load= Rs 55,000 and Transit time = 4 days (North India) and 2 (Maharashtra)

 

Table 4: Percentage Improvements

	Initial system	Proposed system	Deviation	Improvements
Total cost/month	1500000	1320000	180000	12%
Total no of routes	4	1	3	75%
Transit time	6	4	2	33%

 

Table 4 shows the comparison between proposed systems with an initial system to calculate the percentage improvements. We studied a mixed truck delivery system that allows both single hub cross-docking with milk run and direct shipment. A mathematical model was developed to determine the total transportation cost. Computational experiments were carried out to compare the mixed delivery system. From the comparison, it was found that there was 12 % improvement in the overall transportation cost.

 

4.0 RESULTS AND DISCUSSION:

In the study of milk run to pick up with the cross-docking system, it was observed that there was 12 % of cost saving compared to the traditional practice of delivering goods to a customer. When considering only interplants located in Karnataka region. Third party logistic was adapted to do milk run pick, from this number of the vehicle used was reduced from 4 to 2 vehicles. Truck utilization was made more effective as product pick up was by milk run. The 7-ton capacity vehicle was used where there is 100% utilization of vehicle as this automobile industries group dispatches around 6.5 tons on daily basis. Transit time was improved by 33%.Therefore, the production network is associated straightforwardly from purpose of origin(supplier)to purpose of an offer, the ware is moving quicker, the stock costs, taking care of expenses, and working expenses are diminished and a client's in the nick of time requests are better coordinated.

 

In this study, we proposed a milk run to pick up and cross-docking model and compared the results of cost computation with traditional method and proposed the system. Advantages of a milk run operation incorporate enhanced truck usage, payload stacking effectiveness, and diminished movement clog at get together plants, lessened aggregate working expenses and decreased contamination discharged to the earth.

 

5.0 REFERENCES:

1.     Jayaram, J. and Tan, K.C., 2010. Supply chain integration with third-party logistics providers. International Journal of Production Economics, 125(2), pp.262-271.

2.     Cheong, M.L., Bhatnagar, R. and Graves, S.C., 2007. Logistics network design with supplier consolidation hubs and multiple shipment options. Journal of Industrial and Management Optimization, 3(1), p.51.

3.     Aguezzoul, A., 2007, November. The third party logistics selection: a review of the literature. In International Logistics and Supply Chain Congress (p. 7).

4.     Cheong, M.L., 2004. Logistics outsourcing and 3PL challenges.

5.     Sukachai Penpokai, ‘Mathematical model for combined outbound logistics and inbound logistic using milk run deliveries', International Conference on Engineering, Project, and Production Management (EPPM 2013)

6.     Apte, U.M. and Viswanathan, S., 2000. Effective cross-docking for improving distribution efficiencies. International Journal of Logistics, 3(3), pp.291-302.

7.     Arabani, A.B., Zandieh, M. and Ghomi, S.F., 2011. Multi-objective genetic-based algorithms for a cross-docking scheduling problem. Applied soft computing, 11(8), pp.4954-4970.

8.     Lee, Y.H., Jung, J.W. and Lee, K.M., 2006. Vehicle routing scheduling for cross-docking in the supply chain. Computers and Industrial Engineering, 51(2), pp.247-256.

9.     Andreas Nilsson, ‘Opportunity for the implementation of milk run system’, Journal of Industrial and Management Optimization, Volume6, Issue 5, 2010

10.   Dantzig, G.B. and Ramser, J.H., 1959. The truck dispatching problem. Management Science, 6(1), pp.80-91.

11.   Theeratham Meethet, ‘Vehicle Routing in Milk Run Operation’, International Journal of Production Economics, Volume 125, Issue 2, Pages 262–271, June 2010

12.   Meier, J.F. and Clausen, U., 2014. A versatile heuristic approach for generalized hub location problems. Preprint, Provided upon personal request Google Scholar.

13.   Li, Z., He, W., Sim, C.H. and Chen, C.C., 2012. A solution for cross-docking operations planning, scheduling, and coordination. Journal of Service Science and Management, 5(02), p.111.

 

 

 

 

 

Received on 31.01.2018                Modified on 15.02.2018

Accepted on 19.03.2018           ©A&V Publications All right reserved