Environ. Sci. Technol. 1999, 33, 1495-1500
Application of Analytic Hierarchy Process Techniques to Streamlined Life-Cycle Analysis of Two Anodizing Processes PATRICK EAGAN* Engineering Professional Development, Mechanical Engineering, 432 North Lake Street, University of WisconsinsMadison, Madison, Wisconsin 53706 LAURENCE WEINBERG Boeing Company, P.O. Box 3707 (MS 7A-XC), Seattle, Washington 98124-2207
New approaches and tools are needed to enable engineers to assess and deal with the environmental attributes of manufacturing processes. A special concern of adding environmental attributes to products and processes is dealing with the tradeoffs associated with those attributes. The paper demonstrates the utility of the Analytic Hierarchy Process (AHP) when applied to the environmental streamlined life-cycle assessment (SLCA) of two manufacturing processes (chromic acid and boric/sulfuric acid anodizing). Two methods are detailed in the paper and the accompanying Supporting Information. The application of AHP to abridged matrix-based tools adds value to a SLCA approach by providing logical consistency to valuing the matrix cells and increasing the speed of analysis. AHP also provides a built-in check on consistency that enables the user to monitor the various comparison matrixes for logical consistency in assigning numbers to the cells of the matrixes.
Introduction This paper describes an application of a streamlined lifecycle assessment matrix to an environmental analysis of two aluminum anodizing processes. Analytic Hierarchy Process (AHP) is a decision-making approach that has utility in the emerging area of design for the environment (DFE). The analysis will demonstrate the power, nuances, and sensitivity of AHP when applied to streamlined life-cycle assessment (SLCA). For the purposes of this paper, life-cycle analysis is defined to be the analysis of a product, process, or facility’s environmental benefits and burdens that occur during its life-cycle (1-4). Specifically, this paper focuses on the assessment of a manufacturing process. In addition, the use of the terms SLCA and DFE is consistent with Graedel (5). AHP is only one decision theory approach that can have utility for environmental decision making. One of the advantages of applying AHP to SLCA matrix analysis is its flexibility. AHP can be used to establish the relative values (or weighting) associated with each cell of a SLCA matrix or to environmentally compare two or more processes or products. When used in conjunction with a matrix-based * Corresponding author phone: (608)263-7429; e-mail: Eagan@ engr.wisc.edu. 10.1021/es9807338 CCC: $18.00 Published on Web 03/26/1999
1999 American Chemical Society
SLCA tool, AHP is relatively easy to use and in some applications enhances the speed of analysis. The application described in this paper was done at the Boeing Company as a pilot test demonstration of the SLCA technique. The analyses reported here and the development of the SLCA matrixes were developed by a team of pollution prevention process specialists. The analysis was carried out to test the ease of application of the matrix technique and the associated matrix cell questions. An appendix, which appears as Supporting Information, shows all the details of the analysis described in this paper.
Background A critical aspect of environmental product or process design is the analysis of its life-cycle. Most design-for-the-environment activities evaluate to one degree or another the environmental impacts of various life-cycle stages. The resulting tools are evolving. Ideally a method would identify and account for all the environmental impacts of a product or process. The Society of Environmental Toxicology and Chemistry (SETAC) has formalized this methodology and called it life-cycle analysis or LCA. Generally these LCAs have been performed on “simple” products in the United States and Europe. However, LCA has found limited application on complex products. Extensive applications have been hampered by data sufficiency issues, costs, and balancing the accuracy of analysis with decreasing utility associated with that detail (2-4, 6). Faced with the limited utility of life-cycle analysis for complex products, several companies have developed SLCAs or abridged LCA approaches for their design communities. A useful type of SLCA is a matrix-based approach developed by Graedel at AT&T (1, 5). Generic matrixes have been developed for products (7), processes (8), facilities (9), and materials (10). Other design matrixes have been developed as well (11). A special concern of adding environmental attributes to products and processes is dealing with the tradeoffs associated with those attributes. Some environmental attributes come at the expense of others. Is it better to minimize the use of water in Arizona for production at the expense of volatile air emissions? Is it better to locate a manufacturing plant near a source of energy or near a source of production materials? Design engineers when faced with shrinking design cycle times and time pressures will answer these complex questions, and a prioritization process takes place. How to identify those values, assign corresponding weights, and make the values explicit are important and sometimes difficult to perceive. SETAC recognized these issues and outlined a number of methods to deal with valuation, including decision analysis using Multi-Attribute Utility Theory (MAUT), Analytic Hierarchy Process (AHP), and Impact Analysis Matrix (IAM) (12). Design tools that are in a matrix format lend themselves to an AHP approach. This paper will focus only on AHP.
What Is AHP? AHP is a flexible method that assigns weights to various factors in a hierarchical structure by making pairwise comparisons. The method permits comparison of alternatives with respect to multiple attributes. It is particularly useful for complex problems and when values are involved. An AHP user identifies an objective to be attained and alternatives to meet this objective, creates a hierarchy of factors that influence the objective, and populates a sequence of pairwise comparison matrixes using AHP scoring rules. This is illustrated and discussed below and in the Supporting Information. The VOL. 33, NO. 9, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. Process matrix. method has been used in a variety of problems and settings (13, 14) to establish a structured approach for decision making. These include risk analysis (15), cost/benefit studies (16), and conflict resolution (17) to name a few. The AHP approach has a number of features. AHP can be used for sensitivity analysis to see what happens when different values are prioritized. It can be used by individuals or groups. AHP also allows professionals to revisit and refine problem definition and values over time as well as to examine the tradeoffs and values represented by the analysis. The AHP approach assumes that each of the factors under assessment is independent. In practice this is difficult to achieve, but the method can still be applied when there is some degree of interdependence. Saaty has addressed this question of independence in his work (pp 89-90 of ref 14). When the objective is the comparison of two alternative processes using an SLCA matrix, the user has two options. The first consists of computing a weighted, scored matrix for each process and then comparing the resulting matrixes (the Matrix Question Approach). This option permits each process to be examined by itself and may indicate areas of potential process improvement. This approach also could be considered when detailed quantitative information is available for the alternative processes. Another way to attack the problem is to create another level in the AHP structure and to use the AHP methodology to directly compare the two processes (the Direct Comparison Approach). The second option is often faster to apply because it does not require effort where the processes are equivalent in their impact. When less is known about the processes, as is often the case during the early stages of design, the Direct Comparison Approach still permits useful analysis. Direct comparison also addresses some of the problems associated with the use of relative magnitude terms when using the Matrix Question Approach. (See SLCA Matrix Description section below.)
AHP Example Application This paper compares two alternative anodizing processes for the treatment of aluminum. Both processes involve running a current through a bath in which the aluminum part is submerged. Alternative A involves the use of chromic acid as the bath, while alternative B uses a boric/sulfuric acid bath. The principal reason for alternative B is the elimination of chromium chemistry in the anodizing process. Chromium (as chromium VI) is a regulated material with significant environmental and health impacts due to its hazardous nature. Alternative A operates at a lower temperature (with possible cooling requirements) than alterna1496
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tive B, indicating that alternative B may have energy advantages. However, it turns out that alternative B requires better temperature control (it operates in a smaller temperature range), which would tend to favor alternative A with respect to energy considerations. For purposes of this analysis, these two factors cancel each other out; the processes are considered to be equal with respect to infrastructure energy considerations. Discussions with process experts suggested that both processes contributed equally to the weight of products passing through the processes. Hence the impact to energy consumption during the product lifecycle stage (lc6 in Figure 1) was considered to be the same for each process. It is in these seemingly difficult comparisons that decision theory can be helpful. AHP lends itself to performing “what-if” scenarios.
SLCA Matrix Description Figure 1 shows the process matrix, the life-cycle stages, and the environmental concerns arrayed in a six by six matrix (8, 18). Designers using a streamlined matrix approach answer a series of questions associated with each cell of the matrix. These questions are intended to measure the degree of environmental impact arising from the “life stage” in the area of concern. For the process matrix, a typical question for the first row, first column cell would be “Are large quantities of water required to control process under analysis (PUA) process equipment temperature?” Answers to the questions make it possible to identify and score the various environmental aspects of the process in each cell on a 0-5 scale (note that the choice of scale is arbitrary). The sample question also illustrates one of the challenges of this technique, the use of a relative magnitude term like the word “large”. A user should define what will constitute “large” in the context of the application. Other terms such as “significant” or “major” present similar difficulties. Direct comparisons of alternatives can help address this type of semantic problem. The process matrix is intended to be generic and to be applicable to a wide range of processes. However, users should modify the matrix to meet their needs by revising the life-cycle stages, the areas of impact, or both. The meaning of the life-cycle stages used in the Boeing process matrix can be found in ref 8. Environmental scores for processes can be quantified by summing all of the cells in the matrix or showing them as row or column sums. These matrixes can then be used to improve process design, compare design alternatives, or allocate resources to problem areas.
FIGURE 4. Second-level or tier 2 factors.
FIGURE 2. Matrix question approach. FIGURE 5. Final tiersalternatives.
FIGURE 3. First-level or tier 1 factors. Given the raw cell scores based on a series of questions, it is desirable to assign weights to the cells in the matrix with respect to each other. By not assigning weights, the user implies that each cell is equally important. Equal cell valuation has a consequence. For example, the user is implicitly treating the importance associated with nonhazardous materials choices for process infrastructure equal to that associated with energy impacts during process termination. While treating all cells equally may be of interest in a straight comparison of processes, it is not as useful when engineering or managerial decisions need to be made. As a management device, varying the weights for each cell permits management to transmit a vision of importance for process improvement. For example, management may want to emphasize energy reduction and assign higher weights to the cells in the energy column. Figure 2 represents the Matrix Question Approach. Each cell’s unweighted (raw) score is multiplied by the corresponding cell weight to arrive at the cell’s weighted score (the final weighted score). This is not matrix multiplication as it is usually defined. It is in this valuation approach that AHP can be used, consistently and transparently, to develop a weighting factor for each cell with respect to the other cells. The other benefit to this kind of approach is that it makes the values of the tool designers reflect managerial or expert opinion in a very cellspecific, visible way.
Conversion from the Matrix Format to an AHP Hierarchy AHP will be used in the two approaches introduced earlier. Both involve the comparison of two alternative processes. The Matrix Question Approach will use AHP to value the cells in the process matrix of Figure 1 with respect to anodizing type processes. This information will then be combined with the results of individually scoring the matrix for the two alternative anodizing processes to compare these two processes. In the second, the Direct Comparison Approach, the two alternative anodizing processes are compared directly using AHP. This second application will build upon the analysis done for the first application. The first step in the use of AHP is to determine a goal or objective. The authors selected the following objective: Determine the (process) design option with the least adverse environmental impact over the life of the process. The manufacturing process example chosen involves a metal finishing operation (anodizing of aluminum) with a choice between two types of anodizing methods described earlier. The relative valuation of life-cycle steps and areas of environmental concern reflect the choices and values of those applying the tool, as well as the operating conditions that characterize manufacturing at the site. The notation in Figure 3 will be used. For each of these factors, the next level (second level or tier 2) consists of the environmental impact categories shown
FIGURE 6. Process matrix hierarchy. in Figure 4. The final tier consists of the two alternatives shown in Figure 5. Figure 6 represents the hierarchical structure. The selection of the life-cycle stages as the tier 1 factors is not pre-ordained. Using the environmental concerns as the first tier and the life-cycle stages as the second tier in the hierarchy is valid. The user needs to determine which order seems most natural to the analysis. In the analysis that follows, the comparisons were structured so that a higher degree of importance indicated greater adverse environmental impact. Thus, the alternative with the lower score is the preferred choice. This approach avoids semantic problems caused by double negatives.
The Matrix Question Approach Using the AHP methodology, one can create a series of comparison matrixes to display the relative importance of one level of the hierarchy with respect to each of the factors in the levels above. For the anodizing example, the AHP structure of Figure 6 results in one 6 × 6 matrix (for the six life-cycle stages) and six (for the six life-cycle stages), 6 × 6 matrixes (for the six impact areas with respect to each lifecycle stage). These matrixes will be used to generate the weights to be assigned to each cell of the process matrix of Figure 1. In the Direct Comparison Approach, the user would create an additional 36 (for the 36 life-cycle stage/impact area combinations) 2 × 2 matrixes (for the two alternative processes). These matrixes can be found in the Supporting Information. The AHP approach requires a comparison of the factors and their relationship to the impact on the goal. The user performs this comparison by assigning an integer ranging from 1 to 9 or the reciprocal of such an integer to each cell of the matrix to measure the relative importance of the factors that characterize the cell. The cells along the diagonal are given the value 1. The precise description of this scoring mechanism is given in the Supporting Information. If at any stage the user wishes to avoid the admittedly difficult process of comparing factors, then one can assign ‘1’ to every cell, i.e., treat all factors as having equal importance. The user, however, must realize that this choice is itself a statement VOL. 33, NO. 9, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 7. Sample AHP matrixes. of relative value. The values inserted into the matrix will depend on the particular processes being examined, the site where the processes are being implemented, and other similar factors. Although the example involves two alternative processes, AHP will easily accommodate two to seven alternatives. The rationale behind the limitation of seven alternatives is discussed by Saaty (pp 55-57 of ref 19). Figure 7 illustrates two of the AHP matrixes for the anodizing process described above. The entries represent values assigned by the individual or team carrying out the analysis. During the comparison of the life-cycle stages, two factors were kept in mind while doing the pairwise comparison. These were the designer’s ability to influence the life-cycle step and the relative extent of environmental impact of the life-cycle step. In addition, some heuristic rules are provided in the Supporting Information to help compare the various life-cycle stages. From the first matrix in Figure 7, it can be seen that the life-cycle of products that pass through the process under analysis (PUA) was considered to be the most important factor. This reflects the fact that products that pass through the PUA have extended lives. The PUA itself is considered the next most important factor. The pre- and post-PUA manufacturing steps are considered to be of intermediate importance, while the infrastructure and termination steps are considered to be of least importance. The infrastructure stage was given a low level of importance relative to the other life-cycle stages because the process was chemical rather than mechanical in nature, the existing equipment could be used for both processes, and the equipment has a long useful life. Of the six, second tier matrixes, only one is shown in Figure 7. For the infrastructure stage (lc1), energy and solid waste were considered to be the two dominant environmental factors. The Supporting Information shows that the matrixes for the manufacturing stages (lc2, lc3, and lc4) are similar to each other, with energy, hazardous materials, and air emissions as the dominant factors and with energy and air taken as the most important. (Note: Because anodizing process B represents a significant improvement in the area of hazardous material choice, this relative ranking will tend to downplay the advantage of B over anodizing process A.) For process termination, lc5, the residues and energy use are taken to be the major factors, with solid waste as the principal factor. For lc6, energy use is the predominant factor, followed by hazardous materials and the residues. At this point, the AHP pairwise comparison matrixes at the tier 1 and tier 2 levels are complete. The next step is to apply mathematical algorithms to extract the appropriate eigenvalues and eigenvectors that are used to determine the weights to be assigned to the various factors. These weights, in turn, can be used to assign weights to each of the cells in the Boeing process matrixes. If a process is being evaluated by itself, the cells are scored from 0 to 5 and then multiplied by the cell weight as shown in Figure 2. If two processes are being evaluated, each matrix can be analyzed, and the resulting matrixes compared. The user can total scores or add up the sum of the weighted cells. Figure 8 represents the final cell weighting for the anodizing-type processes. The 1498
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FIGURE 8. Anodizing process matrix cell weights.
FIGURE 9. Chromic acid raw scores.
FIGURE 10. Boric/sulfuric acid raw scores.
FIGURE 11. Product of the chromic acid raw scores and the cell weightings (Figure 8).
FIGURE 12. product of the boric/sulfuric acid raw scores and the cell weightings (Figure 8). numbers 0.054, 0.149, 0.290, 0.133, and 0.141.233 represent the column sums from Figure 8. The highest weighted environmental area of concern was energy, corresponding to the value of 0.290 associated with the energy column. At this point, the weights are applied to the cell scores, as determined by the responses to the corresponding cell questions. Each process is now rated, and a user can identify areas for process improvement from an environmental perspective. Figures9 and 10 show the raw scores for the two anodizing processes. Multiplying the raw scores with the cell weights as shown in Figure 8 produces the weighted scores for the two processes shown in Figures11 and 12. A total of the cell scores from Figure 9 (chromic) yields an unweighted score of 87.5. The boric/sulfuric option unweighted score is 73.7. Thus, the boric/sulfuric option has the lower perceived adverse environmental score. If the user
FIGURE 13. Anodizing process comparison process scores combined with tier 2 weights.
Matrix Question Approach. Part of this difference is attributable to different groups carrying out the two different analyses. In addition the Direct Comparison Approach permitted a more refined comparison of the two processes. For example, the Matrix Question Approach offers only a yes/no choice with respect to the use of hazardous materials in the PUA, while the Direct Comparison Approach allows for a greater degree of comparison.
FIGURE 14. Final comparison of anodizing processes A and B.
Matrix Computations
normalizes the scores so that they sum to 1, the corresponding figures become 0.543 (chromic) and 0.457 (boric/sulfuric). Summing and normalizing the weighted scores from Figures 11 and 12 show the scores for the two processes. Chromic acid scored 0.554, and boric/sulfuric scored 0.446. Thus, the weighting scheme has tended to raise the chromic score somewhat and to lower (improve) the boric/sulfuric score, thus increasing the preference for the boric/sulfuric option. In many applications, however, the user is more interested in directly comparing two or more alternative processes rather than analyzing each process separately in a stand-alone mode as done above. In such a case, AHP offers a convenient method to carry out this comparison.
With the advent of user-friendly computational programs such as MatLab and Mathcad, which make use of matrix notation, it is useful to frame the AHP technique as applied to streamlined LCA in the language of matrixes. This is done in the Supporting Information. Other available software includes Expert Choice and Criterium Decision Plus from Infoharvest.
The Direct Comparison Approach Building on the first and second tier weights developed under the Matrix Question Approach, the user now proceeds to directly compare the two anodizing processes against one another with respect to the tier 2 factors for each of the tier 1 factors. This results in a series of 36 2 × 2 matrixes. These matrixes can be found in the Supporting Information. As before, the eigenvalues and eigenvectors for these matrixes can be computed using available software or by developing appropriate computer algorithms, and from these data, weights can be determined for the alternatives. Conceptually, it may be easier to look at the vector of weights for the alternatives as an allocation of points between alternatives. In other words, the user allocates one point between the alternatives for the corresponding life-cycle stage/area of concern. The weighted matrix from the Matrix Question Approach part of the paper can be used to look at the vector weights. It is also possible to build up the final ‘score’ for the alternatives by constructing the appropriate matrixes and using matrix multiplication to calculate this score. It is important to remember that the scores are relative, and they should not be taken as absolute values associated with each alternative. The matrix construction including the application of AHP to allocate points between the two anodizing processes can be found in the Supporting Information. After assigning weights to the Tier 1 and Tier 2 factors and using AHP to compare the alternative processes (see Supporting Information), the alternatives can be ranked with respect to each other. Recall that these are relative, not absolute, rankings. Figure 13 shows a summation of the lifecycle rows. Recalling that a higher score indicates greater adverse environmental impact, a user can see that alternative A (chromium acid anodize) is less environmentally acceptable for each life-cycle stage, or at best, the same as the alternative boric/sulfuric acid anodize. Using weights for the tier 1 factors with respect to the objective, the final matrix (vector) compares the two process alternatives (see Figure 14. On the basis of these two analyses, from the environmental lifecycle aspect, the boric/sulfuric acid process is the better choice. The authors, using the Direct Comparison Approach, gave the boric/sulfuric option greater preference over the chromic process than the pollution prevention team did using the
Discussion The paper demonstrates the utility of AHP in the assessment of two manufacturing processes, chromic acid versus boric/ sulfuric acid anodizing. AHP also provides a built-in check on consistency that enables the user to monitor the various comparison matrixes for logical consistency in assigning numbers to the cells of the matrixes. The AHP technique enables the user to make explicit the values that are embedded in the analysis and thereby provides the reviewer of the analysis with important data on “where the analyst was coming from” when the streamlined LCA was performed. The technique can be applied in a reasonably short period of time, on the order of several hours if speed is required, making it usable in a design environment. AHP is certainly not the only technique that is available to assign weights to the cells of a streamlined life-cycle matrix or to compare alternatives with respect to environmental impact, but anyone who proposes to work in this area should consider the methods described in this paper as possible tools. The application of AHP to abridged matrix-based DFE tools has a number of benefits. These include increased sophistication of establishing weighting values for the matrix cells of an SLCA. The method allows a rational process where panels of external or company environmental experts can set weights in a relatively objective, internally consistent, transparent way. Comparisons of processes can be done very quickly, as is shown in the previous examples. All of these factors add value to the SLCA approach to improving the environmental attributes of products and manufacturing processes.
Supporting Information Available A detailed look at the analyses of the two anodizing processes including a list of the heuirstic rules, the AHP matrix computations, and a description of the necessary matrix manipulations using matrix notation (16 pages). This material is available free of charge via the Internet at http:// pubs.acs.org.
Literature Cited (1) Graedel, T. E.; Allenby, B. R. Industrial Ecology; Prentice-Hall: Engelwood Cliffs, NJ, 1995. (2) Curran, M. A.; Young, S. Int. J. Life Cycle Assess. 1996, 1 (1), 57-60. (3) Ehrenfeld, J. R. J. Ind. Ecol. 1997, 1 (2). (4) Owens, J. W. J. Ind. Ecol. 1997, 1 (1), 37-49. (5) Graedel, T. E. Streamlined Life-Cycle Assessment; Prentice-Hall: Englewood Cliffs, NJ, 1998. (6) White, A.; Shapiro, L. K. Environ. Sci. Technol. 1993, 27 (6), 1016-1017. (7) Graedel, T. E.; Allenby, B. R.; Comrie, P. R. Environ. Sci. Technol. 1995, 29 (3), 143A. VOL. 33, NO. 9, 1999 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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(8) Eagan, P. D.; Weinberg, L. Development of a Streamlined, Lifecycle Design for the Environment Tool for Manufacturing Process Modification: A Boeing Defense and Space Group Case Study. Presented at the International Symposium of Electronics and the Environment, Part of the Conference Record, San Francisco, CA, May 5-6, 1997. (9) Weinberg, L. The Development of a Streamlined, Environmental Life-Cycle Analysis Matrix for Facilities. Presented at the International Symposium of Electronics and the Environment, Part of the Conference Record, Oak Brook, IL, May 4-5, 1998. (10) Allenby, B. R. Environ. Qual. Manage. 1996, 5 (4). (11) Veroutis, A.; Aelion, V. Environ. Qual. Manage. 1996, 5 (4). (12) Society of Environmental Toxicology and Chemistry and SETAC Foundation of Environmental Education Inc. A Conceptual Framework for Life-cycle Impact Assessment; SETAC: 1993. (13) Saaty, T. L. The Analytic Hierarchy Process: RWS Publications: 1990.
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(14) Saaty, T. L. Decision Making for Leaders: RWS Publications: 1995. (15) Mustafa, M.; Al-Bahar, J. F. IEEE Trans. Eng. Manage. 1991, 38 (1). (16) Willett, K.; Sharda, R. Socio-Econ. Planning Sci. 1991, 25 (2), 103-112. (17) Saaty, T. L. Int. J. Conflict Manage. 1990, 1 (1), 47-68. (18) Weinberg, L.; Eagan, P. D. Environ. Qual. Manage. 1997, 7 (1). (19) Saaty, T. L. Multicriteria Decision Making; RWS Publications: 1996.
Received for review July 20, 1998. Revised manuscript received December 8, 1998. Accepted December 8, 1998. ES9807338
