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Selecting Facility Locations and Transportation for ...

  1. 1. Proceedings of the 2008 Industrial Engineering Research Conference J. Fowler and S. Mason, eds. Selecting Facility Locations and Transportation for Multinational Corporation Supply Chains Rocio Escalante and Valerie Maier-Speredelozzi Department of Industrial and Systems Engineering, Gilbreth Hall University of Rhode Island, Kingston, RI 02881, USA Abstract This research incorporates transportation factors into a facility location decision model for multinational corporations (MNC). Previous facility location models have considered the Transportation factor, but typically as a single, simplified component. The Transportation factor is actually complex, with many components such as nodes, routes, costs, time, distance, capacity, and demand. A case study is presented to demonstrate the proposed model. The integration of more Transportation factors into facility location models will transform the interdependencies between the MNC supply chain network and the Global Transportation Network from functional or transactional to a more structural and reciprocal format, thereby enhancing global competitiveness. Keywords Supply chain, transportation, facility location 1. Introduction Multinational corporations (MNCs) want to locate their facilities in regions with characteristics that best suit their needs. The factors they primarily consider are economic cost minimization. The MNCs transform goods from raw materials and also manage a supply chain network that interacts with the Global Transportation Network (GTN) to accomplish tasks associated with goods transfer. Transportation costs are thus relevant to facility location decisions considering that they can potentially increase the MNC’s overall costs. Many factors contribute to facility location decisions [1], but previous facility location models have typically simplified transportation costs into a single model element. The model and case study developed here provide a deeper inclusion of multiple transportation factors. Interdependencies among the MNC supply chain network and GTN are defined as transactional, functional and structural [2]. The integration of more Transportation factors into facility location models will transform the interdependencies between the MNC supply chain network and the Global Transportation Network from functional or transactional to a more structural and reciprocal format, thereby enhancing global competitiveness. Transportation costs represent over 50% of the total logistics costs. Thus, a facility location decision without transportation factors might differ from a decision that includes these costs. If a MNC considers all other factors for their location decision, and at last consider transportation, the company might encounter problems. The MNC would need to invest in redesigning their supply chain network and waste time and money solving unnecessary problems. 2. Effects of Transportation Trends on MNCs Most facility location models are focused on minimizing the sum of all cost related factors. When transportation is analyzed as a contributing factor, it must be recognized that its costs are affected by industry trends or technological innovations. Looking into transportation factors earlier in a facility location decision can help MNCs forecast and incorporate rising transportation costs. Snyder and Daskin [3] suggested that in many cases there might be external changes after facilities are established, such as weather, labor actions, regulations, or transportation costs, that will affect the reliability and cause cost failures to the network. For instance, a MNC might have chosen a location far from developed infrastructure during the 1980’s when fuel prices were fairly low, and nowadays, when fuel prices have greatly increased, their previous location decision might not reflect the best choice. To move goods from one point to another, MNCs normally choose the most economical mode of transportation. Generally, railroads are the least expensive mode followed by truck, which is often more convenient. For 1629
  2. 2. Escalante and Maier-Speredelozzi intercontinental transportation, maritime freight is the least expensive mode, but has longer lead times than airfreight. The cost of these modes can be affected by factors such as weight, time, volume, distance, origin and destination, shipment quantity (Less Than Truckload or Full Truckload), and urgency (Standard, Expedited). Given that rates and volumes are increasing, recent trends show MNC supply chain networks and the GTN collaborating more to obtain higher efficiency [4]. In the U.S., West Coast Ports are working at full capacity and congestion has become an issue. However, if freight is diverted to smaller ports on the East or Gulf Coasts, they would soon also be working at full capacity. Land transportation carriers could be used to relieve the tension in port-to-port congestion. Considering capacity as a factor for facility location decision models helps incorporate the desired structural network configuration, due to the fact that capacity is not an internal component of MNCs and it affects the broader design of another system, the transportation network. This is a consideration that will lead the two systems to be integrated into the same structure. The trends for each mode of transportation from 1980 to 2004 shows how domestic air freight has mostly increased along with truck and rail transportation whereas domestic water freight has decreased in volume [5]. Over time, globalization has caused distances between businesses to increase [6]. This directly affects carriers as well as the MNC’s transportation costs, lead times and probability of delays. The longer distances and the greater variability in transit times require importers to hold more safety stock. Companies often choose to source from Asia where manufacturing and labor costs are lower, but transportation expenses and hidden costs may increase overall costs. A significant percentage of products that are flown from China to the U.S. could be shipped by maritime freight if time was not an issue, but are often expedited by airfreight to ensure schedule integrity. This is a large investment, especially for lower priced manufactured goods. MergeGlobal estimates that 50% of the air freight volume comes from upgrades on maritime shipments due to emergencies. Interviews with China-U.S. shippers regarding reasons for using airfreight over maritime freight showed that 38% of trips are due to emergencies, where demand or due dates would not be met otherwise [6]. Greater risk of loss or damage as maritime freight, unpredictable demand and unacceptable maritime freight transit times were also mentioned. Import demand growth along with insufficient infrastructure has been decreasing reliability and thus, affecting costs. In a survey, thirty percent of MNCs responded that reliability was the most important factor when shipping a product utilizing maritime freight [6]. MNCs reported willingness to sacrifice cost in exchange for trustworthy transportation carriers. Some of the other factors were price, transit times, information availability, customs clearance and carrier relationships. A transportation factor that is not mentioned in this analysis is flexibility. Maritime freight with long lead times has less ability to adapt. If there is demand variability or uncertainty for a specific product and the ship is already underway, there is not much that can be done to expedite or delay shipment arrival times. This not only affects inventory, but also overall system performance and corporate market image. The key to understand how any transportation carrier can be flexible is to consider that they are part of a broader system. Without large investments in new infrastructure or new technology there might not be any transit time flexibility in maritime freight. Therefore, MNCs should look at how to improve what is controllable such as improving land-side efficiencies to make up for time lost during maritime shipment and customs procedures. 3. The Model The model that is developed defines the concept of transportation costs, and allows the user to decide which mode of transportation should be used. It gives a better representation of reality for supply chain product flows. Previous analyses have considered a broader view of the path from components’ suppliers towards the manufacturing facility and finally to the end customer. However, during this trip there is some implicit movement of product and intermediate stopping points. The proposed model reflects the stages between suppliers and customers which allow the transfer of goods and incorporates decisions regarding transportation modes. The method used to solve this facility location problem is based on the Shortest Path Formulation (SPF). SPF was originally created to solve problems where the goal is to find the minimum total distance, but it can also be applied to other aspects of a network, such as cost minimization. The models used to calculate the costs of the MNC network take into account transportation factors such as distance, unit flow and time. To analyze the MNC’s supply chain network and the GTN, the minimum costs for the suppliers’ and the customers’ side are calculated for each potential facility location using various possible transportation modes. The last step is to add the cost of building the facility in each of the possible locations and then the final location is chosen. The system 1630
  3. 3. Escalante and Maier-Speredelozzi is composed of a certain number of suppliers providing raw materials, components and packaging. These are all moved to an incoming port (P1) through land transportation, as seen in Figure 1. A “port” can mean an airport, a maritime port, a train station, a trucking cross dock, or a 3PL company that undertakes all of the transportation costs and responsibilities for an MNC. From the incoming port (P1), everything is moved to the outgoing port (P2), and afterwards to the chosen facility location (F1, F2, F3, etc.). The parameters of the movement of goods between incoming and outgoing ports will vary according to the independent modes of transportation chosen (truck, ship, plane, train, or multimodal). The same sequence follows from the facility towards the customer. The system analyzed is unidirectional with products moving only downstream from suppliers towards the customers. For this model it is necessary that the MNC already has some possible locations for their new facility. The size of the MNCs network and the possible number of paths will vary as the quantity of suppliers, customers, port locations, modes of transportation and facility locations increases. Figure 1: Network Design Figure 1 shows the flow from suppliers through the MNC’s facility to the customers with all the possible paths that a unit could take. Every supplier, as well as every customer, has their own set of ports and options for modes of transportation, which will allow each of these entities to have their transportation decisions made independently from each other but still related to the facility location decision.. Figure 1 shows only a few nodes; however, the number of nodes can be increased as necessary according to the MNC’s actual network. In Figure 1, there is more than one possible outgoing port, more than one possible incoming port and multiple modes of transportation for each pair of ports. It is also possible to find cross over connections between the set of incoming and outgoing ports. For instance, the shipment leaving Port 1 could either go to Port 2 or Port 4 and from Port 3 it can either go to Port 2 or Port 4. Incoming ports refers to the first port which is receiving material from the supplier or from the MNC facility. Outgoing ports refers to the second port which delivers to the MNC facility and to the customer respectively. This model allows the user to decide not only on the location of the facility and the mode of transportation, but also on the ports which are more convenient. No matter what mode of transportation is used for any segment, it is assumed that the beginning and the end of the trip will use a land transportation mode, represented by the letter “T” typed over some of the links. This assumption automatically generates some costs related to the trucking usage, calculated using a standard cost per mile ($/mile). Depending on the locations of the suppliers and customers in relation with the possible facility locations, some of the modes of transportation might be eliminated because of infeasibility. This will benefit the system by reducing the number of options and at the same time the network size. There is a differentiation between the modes of transportation used on each side of Figure 1. Therefore, “k” will represent the mode of transportation that may be selected for the left side of the system and “q” will represent the mode for the right side. The parameters and notation for the model are explained as follows. i – Suppliers j – Possible Facility Locations k, q – Modes of Transportation l – Demand nodes (customers) 1631
  4. 4. Escalante and Maier-Speredelozzi Fij – Unit flow between supplier i and facility j Fjl – Unit flow between facility j and demand node l Qj – Cost of creating facility in location j Ck, Cq – Cost per unit distance per unit demand per time unit for mode of transportation k or q m,n – Incoming and outgoing ports (respectively) for supplier-facility segment o, p – Incoming and outgoing ports (respectively) for facility-customer segment dyz – Distance between node y and node z in Figure 1 (where nodes can mean i, m, n, j, o, p, or l options) twx – Transit time by truck between node w and node x in Figure 1 (where nodes i, m, n, j, o, p, or l are options) tmnk – Transit time between incoming port m and outgoing port n using mode of transportation k topq – Transit time between incoming port o and outgoing port p using mode of transportation q Tc – Cost per unit distance per unit demand of using land transportation  (d ( i , j ,m ,n ) im  d nj )(tim  t nj ) FijTc   (d ( j ,l ,o , p ) jo  d pl )(t jo  t pl ) F jl Tc  (1) d t mn mnk ( i , j ,k , m ,n ) Ck Fij  d t C q F jl   Q j op opq ( j ,l ,o , p ,q ) j The model in Equation 1 calculates the cost for a new facility location decision and the location of the ports which are more convenient. A solution is sought by looking for the minimum cost using Equation 1. The first and second terms refer to the trucking costs at the beginning and the end of each half as shown in Figure 1. Each of these terms is constituted by their respective distance, transit time and flow plus the cost of trucking. The third and fourth terms represent the transportation cost involved between ports for both supplier-facility and facility-customer segments in Figure 1, which will vary depending of which mode of transportation is selected. These terms are constituted the same way as the first two but with the only variation of the cost of transportation referred to the selected mode. These last two terms of Equation 1 define the transportation related decisions. The costs (Ck and Cq) are multiplied by the transportation factors (distance, transit time and unit flow) in order to give a higher weight to the locations with undesired characteristics. Whenever there is an unfeasible match of dimensions, a high value is given to the transit time in order to prevent this option from being selected. The last term refers to the cost of building the facility in the selected location, which is related to expenses for physical space, equipment and construction. 4. Case Study In order to validate the model, several MNCs and distribution and shipping companies, including Company ABC, were approached to obtain real data. Company ABC is an American company who manufactures consumer craft items sold through major retailers within the United States and internationally. Its supply chain involves the movement of products within different countries and continents, from supplies to final product transportation. One specific product was chosen in order to build a representative supply chain and transportation network. The network is built considering a certain number of suppliers, a manufacturing facility, a warehouse and a certain number of customers. Their manufacturing facility is located in Rhode Island and their warehouse is located nearby in eastern Connecticut. They also have a plant in Shenzhen, China that handles part of the packaging. It was difficult to obtain precise data for some aspects. Therefore, some case study costs were estimated based on publicly available information from shipping, transportation, government, and real estate sources. Most of the suppliers are located around the manufacturing facility and the warehouse is located just a few miles away. The proximity shows how the selection of suppliers was made based on the location of the facility, which was built first. Therefore, the possibility of finding an optimal location for the manufacturing facility might create the necessity of looking for different suppliers in order to find a more cost effective region. The way that the decisions are made is a cycle and shows how the locations of both types of entities are dependent on the other. The case study with ABC’s company information is a hypothetical situation where the company wants to relocate their manufacturing facility. Remaining in the Rhode Island location is still an option, and the costs of building the facility there are considered as if no facility existed today. For this case study, two other possible locations for a new facility, in Massachusetts or New York, are screened due to the fact that most of the suppliers are in New England. There is a great amount of variability on ABC’s customer demand. Therefore, the orders that ABC’s company sends to its suppliers are not constant either. Because of this, the unit flow considered between suppliers, customers and the manufacturing facility will be represented by the average amount of units per shipment. Some of the costs 1632
  5. 5. Escalante and Maier-Speredelozzi related to the transportation modes were obtained from shipping companies, which provided the standard prices they manage. However, it is important to consider that MNCs are constantly using services from certain transportation carriers, which allow them to obtain special discounted rates based on their high volumes and regular shipments. Within ABC’s company supply chain network, there are some suppliers within very short distances, and therefore, only trucking and rail services will be considered. If the trucking option is selected, the cost will only reflect the trip from the departure at the supplier location to the arrival in the manufacturing facility, without intermediate stops. Also, there are some MNCs that have railways crossing through their facilities, which would change the model’s logic. The cost associated with this type of facility will be calculated similarly, by skipping the port connection. Comparing the suppliers’ and customers’ sides, there is a difference on the decisions made concerning local or regional transportation issues. For the suppliers’ side, truck is the most used mode whenever the shipped quantities do not justify the airfreight. However, ABC’s company demand to the supplier in New Jersey is higher and validates the use of airfreight. Related to the customers, for intercontinental trips, maritime freight is chosen and for regional trips trucking is selected. For the shipments from California and British Columbia, truck is the best option considering that the cost was calculated on a price per unit basis. Because the demand for these customers is fairly low, the price of air freight is not justifiable even though their locations are on the other side of the continent. It is also important to point out that these modes of transportation suggested are chosen considering that all of the shipments are done in a timely manner. Whenever the MNC has urgent orders, then these decisions may be void. For those cases, airfreight is the most convenient choice, though not the least expensive. For ABC’s company case study, two possible port options were chosen for each supplier and customer, based on their proximity to the correspondent node and capacity availability. The calculations in the case study allow for local and global network optimization. The way the network is analyzed allows the connection of its individual segments and entities, which when considered all together, form the whole system. The mode of transportation between ports decision is made without considering which facility location is ultimately chosen. However, the location of each of the ports is directly related to the facility by the distance and transit times. Therefore, even if the relationship and interaction of the different costs is not explicit, it is contemplated when making the facility location decision. The procedure used to create the Excel spreadsheet that calculates the costs related to each possible path is: 1) Calculate the land transportation costs for each possible facility location per supplier, customer and set of ports. 2) Obtain the minimum of the Step 1 costs for each possible facility location. This gives the set of ports that should be selected for that specific facility location. 3) Sum the minimums calculated on Step 2 for each supplier and each customer. 4) Calculate the cost of transportation (for each mode) for each set of ports for each supplier and customer. 5) Obtain the minimum for the costs in Step 4. This gives the mode of transportation for each supplier and customer. 6) Sum the results from Step 5 for suppliers and customers for each of the possible facility locations. And add the cost for building the facility in each location. 7) Choose the minimum cost. This gives the facility location that should be selected. 8) Based on the decision on Step 7, select the corresponding set of ports and mode of transportation. The preferred facility location is Massachusetts. The mode of transportation and port selections are given in Table 1. Table 1: Results for Modes of Transportation and Set of Ports for Company ABC Supplier Set of Ports Mode of Customer Set of Ports Mode of transport transport NJ Newark – Providence Truck Saudi Arabia Jedahh – Boston Maritime GA Atlanta – Boston Truck CA San Diego - Boston Truck RI Providence – Providence Truck Greece Thessaloniki – NY Maritime MA Springfield – Providence Truck Russia St Petersburg – NY Maritime CT Providence – Providence Truck Switzerland Geneva – Boston Maritime RI Providence – Providence Truck BC Vancouver – Boston Truck ON Toronto – Newburgh Truck CT Hartford – Providence Truck RI Providence - Providence Truck 1633
  6. 6. Escalante and Maier-Speredelozzi It is important to consider both transportation and location aspects simultaneously in order to make an accurate decision. An MNC should decide first what level of detail related to transportation factors they want to incorporate when making facility location decisions. Modes of transportation decisions can vary as a consequence of MNCs dealing with the carriers who manage their transportation needs regularly, considering they acquire special deals or discount rates based on the total volume the MNCs ship. From an engineering economic perspective, company ABC should consider the return in investment when deciding on facility location. The decision of building the facility either in the Rhode Island or Massachusetts site is based in current location and transportation costs. However, if these costs are reflected into a 20 year period, perhaps it would be justified to make a higher investment on the site considering that transportation costs might change over time. 5. Conclusions Facility location problems are unavoidable decisions for many organizations trying to compete globally. This type of problem ranges from a simple facility location problem where the only decision made is where to establish a new plant, to more complex problems that decide on several aspects at the same time, such as inventory, demand allocation, reliability, routes and others. In the past, transportation factors have been considered as inputs to several types of models serving as a multiplying weight; however, these factors have not been considered as decisions. Some of the factors related to the complex concept of transportation are: availability and reliability of diverse transportation modes and infrastructure; existing capacity in links, nodes and transportation modes; reduction of transit times for each transportation mode; maximization of transportation resources utilization; improvement of routing and scheduling performance; climate; community culture; regulations and quality standards; and others, along with the more traditional factors of distance, demand, and cost. In this proposed model, some transportation related information is considered as input parameters in order to make decisions associated with transportation itself along with the facility location decision. For instance, costs and transit times for each of the modes of transportation are used in the model, so that a specific set of ports and a mode of transportation are selected simultaneously with the final location decision. The case study allowed for a basic demonstration of the proposed model for Company ABC. In general, the selected modes correspond to land transportation whenever the distances are reasonable, and airfreight for longer distances. Maritime freight was selected for intercontinental trips but these decisions can be changed whenever delivery time limitations exist. The results expressed for ABC’s company are specific for its network design. It is important to point out that this design, and thus the model, is adaptable not only for the type of industry, but also for aspects such as the MNC’s size, product or country of origin. In summary, this research provides MNCs with a tool that facilitates both location and transportation decisions, by incorporating both aspects in a single model along with the GTN’s perspective. Acknowledgements The authors gratefully acknowledge financial support through the University of Rhode Island Transportation Center and the U.S. Department of Transportation. References 1. Escalante, R., Maier-Speredelozzi, V., Hamilton, M., 2007, “Considering Transportation as a Factor in Facility Location Decisions for Multinational Corporations,” Proceedings of the Academy of International Business Midwest Conference, March, Chicago, Illinois. 2. Hamilton, M., 1998, “The Competitive Nature of Global Transportation Networks: A Dynamic Capabilities Perspective,” Presented at the Academy of Management Meetings, August 13-16th, Atlanta, Georgia. 3. Snyder, L. V. and M. S. Daskin., 2005, “Reliability Models for Facility Location: The Expected Failure Cost Case,” Transportation Science, Vol. 39, No. 3, pp. 400-416. 4. Industrial Engineer, 2007, “Higher transportation costs alter distribution: greater collaboration between shippers and carriers results,” IE Industrial Engineer, 2007, pp. 3. 5. Bureau of Transportation Statistics, 2006, “Freight in America: A New National Picture,” January. Accessed March 9, 2007. 6. Clancy, B. P. and D. F. Hoppin., 2005, “Coping with Uncertainty: How might market forces create new ocean transport products for service-sensitive container shipments?” MergeGlobal. Uncertainty_WP.pdf. Accessed February 1, 2007. 1634