USING THE COST-EFFECTIVENESS ANALYSIS IN THE OPTIMAL SELECTION OF PRODUCTS

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1 Balkan Region Conference on Engineering and Business Education & International Conference on Engineering and Business Education Sibiu, Romania, October, LBUS USING THE COST-EFFECTIVENESS ANALYSIS IN THE OPTIMAL SELECTION OF PRODUCTS Vasile, Caruţaşu 1 Sorin, Cristea 2 and Daniela, Caruţaşu 1 Nicolae Balcescu Land Forces Academy, vcarutasu@armyacademy.ro 2 Romanian-German University, cristearoger@gmail.com 3 Nicolae Balcescu Land Forces Academy, vcarutasu@armyacademy.ro 3 ABSTRACT: This type of analysis is performed when the most convenient offer has to be selected out of a wide range of products having the same utility. The model offered by decision trees is a useful tool for the accomplishment of the cost-effectiveness analysis. The most important stage of this approach is the one establishing criteria, sub-criteria and their weights in order to identify, analyze and describe the qualities this type of product has to present. Once this stage has been accomplished, we have to consider the cost of the products analysed. An important stage that can radically change the result of our analysis is the one establishing product costs out of a wide variety of offers by considering only the acquisition cost or the lifecycle cost for the type of product analysed. This study does not only present a software which makes it possible to perform such analyses and to automatically hierarchize offers by modifying the weights given to cost and benefit respectively, but also offers the possibility to perform a sensitivity analysis. 1. INTRODUCTION The modern battlefield has recently become digital and automated, the military structures have gained greater autonomy in action through fast, decisive and dynamic manoeuvres, the armaments as well as the logistic bases have been modernized, and the military have been trained to the highest standards so as to be capable of using the available equipment and to successfully accomplish missions. In all the fields of activity, including the military one, the equipment has turned more and more sophisticated (more complex, wider spectrum of operations), the costs having also grown accordingly. Thus, such expensive equipment should not be purchased without a careful analysis so as to choose the best option in terms of cost-effectiveness. These analyses should be performed by teams of experts who should identify the criteria (requirements) to be taken into consideration when analysing the offers, establish their weights [1], and determine equipment s costs in general and the lifecycle costs in particular. The Romanian army has lately acquired complex combat systems (planes, frigates, etc.) so as to become operational (replace the old and obsolete equipment), to use technology compatible with that of NATO member states and to achieve interoperability with NATO member states armies, given the need to develop joint common missions in different theatres of operation all over the world. The objective of this study is to perform a cost-effectiveness analysis on a complex armament system, in order to emphasize the stages of such a study, and the way sensitivity analysis is performed depending on the allocated funds and on the characteristics specific to the equipment of the Romanian Army. Such analyses should usually be backed up by other models [2] and [3], in this particular case the alternative being the decision-making-under-certainty-conditions model, so as to double-check the optimal solutions obtained in order to see if the two models are identical or at least similar. This study will consider the acquisition of a tank, the stages to be followed in this respect being as follows: establish the criteria, sub-criteria and all other further details, if necessary; establish the weights of the identified criteria and subcriteria; establish the acquisition costs of all the tanks considered for analysis; establish the lifecycle costs of each tank considered for analysis (maintenance, spare parts, operationalization costs, etc.); obtain the optimal alternative; perform sensitivity analysis (to modify both the costefficiency ratio, and the variance of criteria and sub-criteria weights). 2. MATHEMATICAL MODELLING The new missions and challenges of modern armies, the uncertain and rapidly changing operational environment reemphasizes the importance of a technological advantage over the adversary. The new technology entailed on the one hand more dynamic combats, complex and unpredictable actions, and on the other hand higher acquisition and operationalization costs. The decision making process is more complex and requires superiority in the informational domain, a fact that stands true in all the fields of action and even more so in the military one [4]. Given the costs of this state-of-the-art equipment, aspects such as the following are more and more often referred to: using modelling and simulation in order to establish the optimal combat waging strategies; making an optimal use of combat means and ammunition; designing and using specialized software that supports the decision-making process. By using adequate analysis models for the study of phenomena and processes, we can improve them and make them better contribute to the decision making process [5], [6] and [7]. Moreover, by using specialized software we can determine the optimal solution, minimize decision time, perform sensitivity 275

2 analyses and rapidly determine the optimal solution, depending on the system s state parameters [8] and [9]. One of the models used in the decision making process is the decisional tree model. DECIMAK, a specialized software that allows a comparative analysis of equipment, has been developed based on the above mentioned model. It allows us to: assess the efficiency of the equipment considered for analysis; classify the equipment based on acquisition and lifecycle costs; perform sensitivity analysis: when the weight of criteria and sub-criteria are modified; when the efficiency-cost ratio is modified. This program is particularly useful for such analyses and, as we have already mentioned, it allows us to obtain the optimal solution and to perform sensitivity analyses which would otherwise be extremely time-consuming. Adaptability is this program s most important characteristic and it means that this program can be used for other types of analyses as well. For instance, if we want to determine an optimal route, all we need to do is introduce the criteria and sub-criteria and replace cost with route difficulty. 3. ASSESSMENT OF TANK MODELS As we have already mentioned, the Romanian Army has currently taken up an acquisition programme meant to make the equipment compatible and inter-operable with NATO member states armies, within the programmes established by the Ministry of National Defence. Even if the Romanian Army does not dispose of more tank models, the national TR 85M1 tank being the only one available, we can still draw a comparison between the latter and other tank models from different countries. The technical-tactical characteristics to be taken into account when establishing the efficiency of the tank models considered for analysis are as follows: crew; dimensions and weight (weight, length, gun forward, hull length, width, height); armament (main gun, ATGW, machine guns, elevation range, traverse range); ammunition load (main gun, machine guns); mobility (engine, engine power, maximum road speed, range); manoeuvrability (gradient, side slope, vertical step, trench, fording, fording (with preparation)). The tank models considered for analysis are as follows: Type 99; Leclerc; Leopard 2A6; T-80U-M1 Bars; Challenger 2; M1A2 Abrams. Most of the technical-tactical characteristics have been retrieved from the site If the information we needed were not available on that site, we searched for each particular item on other sites. The most difficult task we had to overcome was to find out tank prices, and we have managed to retrieve that information partly from the sites [11]-[17], partly from the individual acquisition contracts. The prices for a specific tank model can differ depending on the acquisition contract. Where prices have not been available we have used the prices for older tank models, depending on the available information. An important characteristic is that all tanks are in fact revised versions of older tanks. Another important characteristic is that tanks have different equipment classes, depending on the mission environment. Last but not least, the price of such a combat means can also vary depending on the number of units it attends, provisions on these aspects being clearly stated in the acquisition contract, which stipulates that issues such as personnel training, spare parts or production licences depend on the number of units attended by such a piece of equipment. Please note that, for the reasons already mentioned, the costs included in the last line of table 1 are based on estimates of actual prices. This is an aspect that can very easily be solved, once the request for offer is filed. An interesting case is that of the Chinese tank model Type 99, which has a very low price and at the same time, a very high performance. Taking into account all the remarks we have made on how data relative to tanks technical-tactical characteristics have been established (information on the same characteristics) and on how tank prices have been decided upon, the final values are presented in table 1. As far as table 2 is concerned, we have left out the parameters with the same value for all tank models, whereas those with too much information have been broken down into several subcriteria (as for example the parameters referring to armament or ammunition). The weights of criteria and sub-criteria have been established by specialists and are in concert with the missions of the Romanian Army. The data will be introduced into the program only after the decision matrix has been normalized, depending on the type of criteria: if the criterion is of minimum, then the normalized value is calculated according to the following formula: a j max aij rij = (1) a a j max j min if the criterion is of maximum, then the normalized value is calculated according to the following formula: aij a j min rij = a j max a j min (2) where: a ij is the element of the decision matrix specific to the mission i and to the criterion j; ajmax is the highest value of the decision matrix specific to the j criterion; ajmin is the lowest value of the decision matrix specific to the j criterion. The normalization stage is a method used for standardizing the values corresponding to the different measurement units of the criteria the analysis is based on. The normalized values are included in table 3, depending on the criteria (minimum or maximum). 276

3 Table 1. Analysed tanks technical-tactical characteristics and estimate costs MODEL Type 99 Leclerc Leopard 2A6 T-80U-M1 Bars Challenger 2 M1A2 Abrams Entered service after Crew 3 men 3 men 4 men 3 men 4 men 4 men Dimensions and weight Weight 54 t 54.6 t 62 t 46 t 62.5 t 62.5 t Length (gun forward) 11 m 9.87 m 9.97 m m m m Hull length 6.86 m 6.88 m 7.7 m m 8.33 m m Width 3.4 m 3.71 m 3.7 m m 3.52 m m Height 2.2 m 2.92 m 3 m m 2.49 m m Armament Main gun ATGW Machine guns 125-mm 9K119 Refleks (AT-11 Sniper) 1 x 7.62-mm, - 10 to mm 120-mm x 7.62-mm, - 8 to x 7.62-mm 125-mm 9K119M (AT-11 Sniper- B) 1 x 7.62-mm, - 5 to mm rifled 120-mm x 7.62-mm 2 x 7.62-mm, - 9 to to to + 20 Elevation range Traverse range Ammunition load Main gun 41 rounds 40 rounds 42 rounds 45 rounds 50 rounds 40 rounds Machine guns x 7.62, 300 x x 7.62, x x mm Mobility x 7.62, 450 x x 7.62-mm x 7.62, x 12.7 Engine Diesel engine Diesel engine Diesel engine Gas turbine engine Diesel engine Gas turbine engine Engine power hp 1500 hp hp 1250 hp hp 1500 hp Maximum road speed 80 km/h 71 km/h 68 km/h 70 km/h 56 km/h 67 km/h Rang 400 km 550 km 500 km 400 km 500 km 425 km Manoeuvrability Gradient 60% 60% 60% 60% 60% 60% Side slope 40% 30% 30% 40% 30% 40% Vertical step ~ 0.8 m 1.25 m 1.15 m 1 m 0.9 m 1 m Trench ~ 3 m 3 m 3 m 2.85 m 2.34 m 2.7 m Fording ~ 1.2 m 1 m 1 m 1.8 m 1.07 m 1.2 m Fording (with preparation) 5 m 4 m 4 m 5 m 3-4 m 2 m COST 2,5 mil $ 6,09 mil $ 5,7 mil $ 5 mil $ (T-80B) 7,6 mil $ 4,3 mil $ 277

4 Table 2. Data considered for analysis. Table 3. Normalization of data introduced in table 2, depending on the type of criteria and subcriteria. 278

5 4. DETERMINING THE OPTIMAL SOLUTION All the data in table 3, criteria, sub-criteria, weights, technicaltactical characteristics and the costs associated with them are introduced into the computer program, as it can be seen in figure 1. Figure 1. Main menu and input data By using the M command we get a graphical representation of tank models effectiveness, the total effectiveness as well as the effectiveness of each criterion and sub-criterion being displayed (figure2). Figure 3. Cost-effectiveness analysis in the case of a 50/50 ratio It follows that the best tank model in this case is the Chinese one, given both its low fabrication costs, as compared to other models (we have considered the entire lifecycle costs as an analysis based only on the acquisition costs would result in a different hierarchy which would not accurately reflect the actual costs of the equipment considered for analysis), and its effectiveness. The cost-effectiveness ratio can automatically be changed by dragging the cursor over the cost-effectiveness button. Figure 2. Measurement of tank effectiveness As it can be seen the most efficient model is the French LECLERC model which has an effectiveness coefficient of By using the C command we get a graphical representation which compares all tank models by taking into consideration both cost and effectiveness, the ratio between them being equal (figure 3). Figure 4. Cost-effectiveness analysis in the case of a 12.5/87.5 ratio As it can be seen in figure 4, in the case of a 12.5/87.5 ratio, the Leclerc French model becomes as efficient as the Chinese one and can thus be the optimal solution as well. An in-depth analysis should also refer to the optimal solution when the criteria and sub-criteria weights are only slightly modified. It is not now the right time and place for an in-depth analysis, studies such as these being included in the acquisition documentation. As we have already mentioned, the acquisition documentation should also include a comparison between models. 5. CONCLUSIONS The programs we have presented are user-friendly and help us to obtain efficient results for military missions and not only. With the help of these mathematical models the best action 279

6 options can be determined, the decision maker having the possibility to choose the most favourable option for mission accomplishment. Our analysis reveals the importance of using an adequate model when thoroughly studying processes and phenomena. Such a model should however be backed up by a specialized software that automatically processes data and obtains realtime solutions. It is also important to use more models (if possible) in order to validate the optimal solution. Last but not least, the software we have presented can be adapted to be used for other types of analyses as well. 6. REFERENCES Cristea, S., Asupra sintezei optimale a tablei de blindaj, A VIII-a Sesiune de comunicări ştiinţifice a Academiei Forţelor Terestre, Eficienţă şi calitate în învăţământul superior, pp , Sibiu, Romania, (2004) Hampu, A., Căruţaşu, V., Cercetări operaţionale cu aplicaţii în domeniul militar, Editura Universităţii Lucian Blaga, Sibiu, Romania, (1999). 5. Carutasu, V., Barsan, G., Aplicatii ale modelarii si simularii actiunilor militare, Editura Academiei Fortelor Terestre, Sibiu, Romania, (2006). 6. Eppen, G.D., Gould, F.J., Schmidt, C.P., Moore, J.H., Weatherford, L.R., Introductory Management Science. Decision Modelling with Spreadsheets, Prentice Hall, USA, (1988). 7. Mureşan, M., Văduva, Gh., Războiul viitorului, viitorul războiului, Editura Universităţii Naţionale de Apărare, Bucureşti, Romania, (2004). 8. Căruţaşu, V., The Using of the Mathematical Models in Acquisitions, Sesiunea de comunicări ştiinţifice a Universităţii Naţionale de Apărare cu participare internaţională, pp , Bucureşti, Romania, (2006). 9. Clauss, F.J., Applied Management Science and Spreadsheet Modelling, Wadsworth Publishing Company, USA, (1986). 10. Popescu, M., Apostol, V., Grad, V., Optimizarea repartiţiei mijloacelor de foc pe obiective, Editura Militară, Bucureşti, Romania, (1989) Type_ Czo.C5.82gi_.C5. 9Awiata_page_12_ rof 280