Because the company is situated far away from its international customers, it is extremely important to have cost-effective logistics solutions and to build logistics confidence that proves the company is a reliable supplier. The latter is reflected in the company's motto: "Always in time!"

The company is the plant flagship of the Omya Group, headquartered in Switzerland. The Omya Group is also a majority owner of many of the ships in the tank-ship fleet. The Norwegian shipping company Anders Utkilens Rederi (AUR) is the other shareholder of the fleet.

The tank ships have various sizes from 2,400 metric tons to more than 19,000 metric tons. When using the larger ships the shipping cost per ton can be 60 percent lower than for the smaller ships.

The ships can be used in the spot market when they are not transporting slurry for Omya Hustadmarmor. For example, after a ship has delivered slurry to a tank farm in Sweden or Finland, it can often pick up methanol in Russia before heading out of the Baltic Sea to Western Europe. AUR is responsible for the spot-market trading.

Operational Challenges


Distribution planning at Omya Hustadmarmor is a complex puzzle. To fully utilize the capacity of a large ship, it is necessary to transport multiple slurries on the ship. Planners must therefore coordinate replenishments of different slurries. Because of limited capacities in production, storage and transportation, it is also important to look at the whole picture and coordinate among the different tank farms. Planners must take into account several domino effects. For example, the choice of product mix for one ship will restrict the possible product mix for the next ship leaving the plant. If the company ships too much of a given slurry on the first ship, it may have too little of this slurry available at the factory for the next ship.

Distribution planning must also be closely coordinated with production planning. When production is changed from one slurry variant to another, the workers must spend some time fine-tuning the production process before achieving the right quality of the new slurry. This changeover time consumes production capacity. Hence, production efficiency depends on the plant's producing large production lots with few changeovers between slurries.

Because of uncertainty of input data, planners may be forced to revise their plans. For some slurries and some customers, demand varies considerably from one week to the next. On the supply side, ships may arrive late at the plant or at tank farms because of bad weather, or they may also become temporarily unavailable because of transportation work for external customers on the spot market.

Omya Hustadmarmor's operations have grown in complexity over the years. In the early 1980s, yearly production volume was less than 200,000 metric tons, and there was on average one ship per week from the plant. Twenty years later, yearly production volume had increased to more than three million, with on average a ship per day from the plant.

For many years, the company scheduled shipments from the plant to the tank farms manually through an informal and unstructured process that involved the Omya sales office in Germany, the local tank-farm managers, the spot-market trader at AUR and the logistics department at Omya Hustadmarmor. The planning was not centralized, and nobody had the complete overview of the situation. Whenever the inventory for one of the products (the "order-triggering slurry") at a tank farm reached an informal re-order point, the Omya sales office tried to order a ship of the appropriate size. The shipping company AUR then had to provide a suitable ship on short notice. Since slurry transportation from Omya Hustadmarmor is the backbone of AUR's business, it had to keep one or more ships within a reasonable distance from the plant in case it needed a ship to transport slurry. This safety-first practice limited AUR's revenue from the spot market, but was necessary given the lack of predictability at the time.

Omya Hustadmarmor tried to cope with the growing complexity by "buying its way around the problem." There were continuous investments in new production, storage and transportation capacities. The planners tried to maintain operational flexibility by using mainly small ships, but the continuous investments and the use of small ships created a financial burden for the company. The company's profitability was also threatened by increasing costs for electricity, fuel, raw materials and other inputs. Steep price increases of the finished products seemed unavoidable, unless the company could improve its supply chain planning.

Around 2000, the company decided both to limit further investments in capacity and to use large ships much more extensively. As could be expected, it encountered problems caused by the reduced flexibility. A changed departure date, destination or product mix for a large ship creates severe domino effects. In response to difficult situations, the distribution planners often had to change the distribution plan in such a way that the production planner was forced to change also the production plan, which led to reduced capacity utilization and to quality problems. The production planner had little influence over the distribution plan, and the planning horizon was only seven to 10 days.

O.R. to the Rescue


At this point in time, the stress at different levels and within different functions of the organization had become unbearable. The top managers at Omya Hustadmarmor realized that they needed help and agreed with O.R. researchers at Molde University College and Optimal Logistics to pursue more cost-effective solutions.

It was very important for the research team to get a deep understanding of the supply chain and operations of the company. First, we performed a preliminary study where our main focus was to analyze customer demand and to identify the key performance drivers in Omya Hustadmarmor's supply chain. The demand analysis revealed that there were a few demanding customers that created disturbances. We recommended increased safety stocks of the slurries bought by these customers at the tank farms and reduced safety stocks for some other slurries.

Further analysis showed that the shipping from the plant to the tank farms was the key performance driver in the supply chain, partly because of its great cost and the freight structure's economies of scale, and partly because the lack of proper planning tools led to unpredictability and low responsiveness.

Developing a planning tool for ship transportation would be the key to stabilizing and improving the company's whole supply chain. Planning would need to simultaneously handle both managing inventories at the tank farms and routing ships. Hence, we agreed upon developing an optimization-based decision support tool for inventory routing, a tool that could enable Omya Hustadmarmor to manage the logistics challenges at a competitive cost. To get the maximum out of the planning tool it would also be necessary to centralize the planning function.

Modeling the Planning Problem


It was important for us to understand and model all the practical constraints of the problem, such as storage capacities at the tank farms, minimum shipped quantities, availability of ships and loading capacity at the plant quay. A key contributor to the development of the DSS was the distribution manager at the time, Geir Teistklub. His willingness to use innovative operations research approaches was a key success factor, and he ensured that the DSS being developed could really match the complex reality that the planners were facing every day.

The goal of the planning is to determine, for each tank farm, which ships should deliver, when they should deliver and how much of each slurry type they should deliver. Hence, the decision variables of the optimization problem correspond to the ship schedules and the shipment quantities.

First, we modeled the optimization problem as a mixed-integer linear program, and tried to solve it using a standard solver. Only small instances were solved optimally, and for larger instances we could not find a feasible solution even after several hours.

These are some characteristics that make this inventory-routing problem difficult to solve:

• Discrete and continuous variables. A well-known difficulty when solving most inventory-routing problems is the combination of large, continuous variables (shipment quantities and inventory levels) and discrete variables (choice of routes and ships). A consequence is that one obtains poor bounds with linear relaxation of the integer linear programming model. Standard solvers are not efficient for these types of problems.
  
  
• Multiple products. Inventory-routing researchers usually assume single products or single families of products, but in our case we needed to explicitly manage multiple products. This made it difficult to disconnect the optimization of the shipment quantities and of the ship schedules.
  
  
• Time-varying demands. Because product demands are dynamic, shipment quantities of the various products may naturally vary from one shipment to another. Cyclic, repetitive schedules are normally either non-optimal or infeasible.
  
  
• A heterogeneous fleet of ships. Inventory-routing researchers usually assume that all ships are homogeneous. In our case, there was a strongly heterogeneous fleet of ships. We therefore needed to consider simultaneously the optimization of shipment quantities and ship schedules.

The problem is complex, but the planners need to obtain solutions relatively fast. A further challenge in designing the solving procedure for the model is that the solutions have to "look good." For instance, when possible, it is preferable to avoid having a ship wait between two shipments. To answer these needs, we developed a specialized metaheuristic procedure based on a memetic algorithm, also called a genetic local search or hybrid genetic algorithm. The last version of the algorithm is able to find very good solutions in a few minutes.

The Decision-Support System (DSS)


The DSS requires various input data, such as inventory levels, forecasted demands at tank farms, transportation costs, travel times, and ship data like capacities and number of tanks.

Planners can incorporate their practical insight by manually changing and freezing some shipments before optimization takes place. This ability is particularly useful in coping with such random events as ship delays or in discussing schedules with the shipping company or the production department.

The system produces different forms of output, which are useful in interacting with the various actors in the supply chain. Omya Hustadmarmor provides the shipping company with the planned routes of the ships, and it provides tank-farm managers with the planned future inventory for each product at each tank farm. The planner can visualize, for each product in the tank farm, whether the planned inventory lies between the safety stock level and the maximum inventory level given by the storage capacity at the tank farm. The DSS can simultaneously show the inventory levels for all products at a given tank farm. Planners use this view, with the list of ships arriving at the tank farm during the planning horizon and their contents, in discussions with the tank-farm managers.

Practical use of the DSS


The DSS supports decisions both at the operational level and at the long-term strategic level. At the operational level, planners use the DSS on a daily basis to ensure that changes in input data do not create problems. The planning horizon for this use is 28 days. The distribution planner and the production planner sit together and, using the DSS, try to find a cost-efficient distribution plan that is also acceptable with regards to production efficiency.

One important purpose of the DSS was to improve supply chain reactivity and control. The planners should be able to re-plan quickly in case of ship delays, machine breakdowns and other sudden interruptions.

In 2004, Omya Hustadmarmor experienced three simultaneous incidents that illustrate the DSS' capabilities for recovery from problems associated with operational accidents. One of these incidents happened in the North Sea, when the ship Kilstraum collided with a submarine that suddenly surfaced in the middle of the night. Kilstraum could continue to the nearest port, but was taken out of service in order to be repaired. At the same time, the ship Bergstraum suffered from engine problems and had to be taken out of service, too. To make matters worse, the company also experienced some machinery breakdown at the plant.

By using the DSS, the planner could immediately see the impact on the distribution plan, create a new plan and secure the deliveries without disturbing the production plan, and without any cost increase. Before the DSS, such an extreme situation would have delayed deliveries and could have damaged customer relationships.

Current logistics manager Geir Teistklub states, "Thanks to the DSS, the work is now much more efficient and predictable. The planners can react fast and correctly if something happens."

We created a special version of the DSS to be used as a simulation tool to analyze different scenarios and study the long-term effects of various strategic decisions. It differs from the operational version in having a longer planning horizon. The company has used this version of the DSS in making its decisions to acquire new, larger ships and to enter the North-American market. Ulrich Koester, head of Global Sourcing in the Omya Group, explains: "We identified, based on various simulations with the DSS, that the ship fleet composition showed a lack of capacity in large ships. That's why we have worked on the next generation of ships. The DSS will allow us to use ships which would not have been feasible with manual planning."

Impact


We implemented the DSS in 2003-2004, and it gave immediate and sustainable positive effects. According to Ulrich Koester, the short-term changes in the distribution plan went down from 18 to two per month. As a result of the increased reliability of the distribution plan, the changeovers in production dropped by 40 percent. Savings in production costs from reduced waste, raw materials and energy consumption total $4.3 million per year. Production capacity utilization increased by 4 percent, making Omya Hustadmarmor able to avoid investments in the production equipment of nearly $13 million.

Volume shipped in large ships has increased from 39 percent to 65 percent, reducing annual transportation costs by more than $1.8 million. This has also had a very positive environmental effect because total fuel consumption has dropped by 12 percent. Large ships consume approximately 40 percent less fuel per ton transported than small ships.

Thanks to the DSS, Omya has also improved its utilization of existing storage capacity at the tank farms. Without this improvement, the company estimates that it would have had to invest in 14,000 cubic meters of new storage tanks.

Because Omya Hustadmarmor's need for transportation capacity has become more predictable, the ship owners' risk when trading on the spot market has been reduced. This has allowed more spot business, increasing the yearly spot-market revenues by more than $600,000. The Omya Group benefits from this increase because it is a partial owner of the fleet.

Altogether, the project and the resulting DSS led to a reduction of about 5 percent of Omya Hustadmarmor's total costs.

Sturla Steinsvik, CEO of Hustadmarmor AS, concludes: "Thanks to this O.R. based tool, the stress and frustration in our logistics function is gone. The logistics team enjoys working with the tool, and our logistics function has become a strong competitive advantage. The DSS strengthens Omya Hustadmarmor's position as the preferred partner in the future."



Stéphane Dauzère-Pérès (dauzere-peres@emse.fr) is professor at Ecole des Mines de Saint-Etienne, where he heads the Manufacturing Sciences and Logistics research team of the Microelectronics Center of Provence.

Atle Nordli (atle.nordli@optimal-logistics.no) is associate professor at BI Norwegian School of Management and founder of Optimal Logistics.

References

1. S. Dauzère-Pérès et al., 2007, "Omya Hustadmarmor Optimizes Its Supply Chain for Delivering Calcium Carbonate Slurry to European Paper Manufacturers," Interfaces, Vol. 37, No. 1, Jan-Feb 2007, pp. 39-51.

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