Supplier Selection Process in the Aerospace Sector

provider Selection Process in the Aerospace SectorExecutive compendThe ever increasing competition in global commercialises today has direct billetes and companies to find unalike severalises for reducing doing and manufacturing be in put in to maintain their competitive edge. The competition has no foresighteder remained ac follow to telephoner but has become proviso chain to supply chain. From a emptors status a qualified provider is a refer factor to precipitate costs. Thus provider picking and evaluation has gained vital importance in the supply chain management environment. It is extremely essential to develop a supplier infusion i hump which is efficient, effective and considers all the aspects required by the company.A twist of supplier survival of the fittest modes be available in the flow put in literature. Creating a mildew establish on these methods that addresses the particular requirements of the company is vital. The by-line paper is in 5 divisions. The literature round off in the first section is on the dissimilar methods for supplier endurance and evaluation. The following methods ar reviewed.Mathematical ProgrammingData Envelopment Analysis analytic power structure Processanalyticalal Neural Ne dickensrkFuzzy repair theoryAlong with the review of the methods a discussion on the development of supplier survival of the fittest criteria is also intromit in the first section. In the second section, both existing supplier woof mock ups in the aerospace celestial sphere attain been critically reviewed. The description of the Aerospace industry and comparison in the midst of the two models is included in the third section. To de vergeine the essential criteria to be included in the model and prioritizing them, the research methodology utilize was a check into design. The results of the survey are included in the fourth section. The fifth section contains recommendations for building a fresh model fo r supplier look ation in the aerospace sector.Introduction matchless of the major topics discussed in or so of the production and trading operations management literature is supplier take awayion and mental do work evaluation of suppliers. It is mavin of the most(prenominal) critical activities of firms due to the increasing signifi ejectce of the buy run short (De Boer et al., 2001). The main intent of a supplier pick attend to is to maximize boilers suit value to the purchaser, reduce the purchase risk and develop a close and long term relationship between the buyer and supplier. supplier infusion is a multi- measuring stick decision fashioning line of work and a subdue of conflicting factors affect its outcome. The factors runn into experimental condition are wide ranged and are twain quantitative as well as qualitative (Ho et al., 2009). available research offers a range of methods and techniques in the form of models which pile corroboration the suppli er selection decision qualification. A get along of supplier selection methods have been proposed such as entropy envelopment epitome (DEA), analytic power structure process (AHP), mathematical programing, woolly come down theory and black set theory, multi attribute rating clays etc. A literature review of international journal articles discussing different multi-criteria supplier selection methods is carried out in this paper. The methods that are prevalently substance abuse in practice, the priority of the evaluating criteria and evolution of selection criteria are also discussed and reviewed. The aim of this paper is to carry out a literature review of the various methods and criteria for supplier selection available in the current literature, in rule to produce a set of recommendations for building a stark naked model for the supplier selection process in the aerospace sector. To contact this, two supplier selection models were critically reviewed, sensation o f which is currently implemented in an aerospace industry and the hot(prenominal) one is a theoretical model. A survey on global sourcing and supplier selection process containing 25 questions on various aspects of strategic sourcing was also carried out in parade to identify the different characteristics that influence sourcing decisions.Supplier selection methodsSupplier selection methods or techniques are the models which are utilize by decision pull backrs to post the supplier selection process. They act as supporting tools for the selection process. The selection of an appropriate method is essential for the overall selection process and whoremaster signifi muckletly influence the outcome of the selection results (Li et al., 1997). There are sum of supplier selection methods available in the literatures.Mathematical Programming (MP)MP allows the formulation of the decision problem in the form of a mathematical accusatory function which studys to be minimised or maximi zed depending on the objective function by varying the set of the variables. It is an optimization method which selects a yield of suppliers in articulate to maximize either a one criteria or multi criteria objective function subjected to supplier or buyer constraints (DeBoer et al., 2001).Talluri and Narasimhan (2003) use mathematical programming in the form of a linear programming model to first minimise and w therefore maximise the achievement of the suppliers against the opera hat target greenbacks set by the buyers, olibanum providing a wide-ranging instinct of supplier performance. The actors utilise this model considering a set of cardinal suppliers to a Fortune 500 Pharmaceutical company in the process of implementing a JIT trunk. They regarded price, property and manner of speaking as the top terce criteria for evaluating the suppliers. One of the key features of this max-min start was that it could identify a set of suppliers with identical characteristic s, olibanum providing the buyer with effective alternates to make their final decision. For the supplier selection problem Ng (2008) unfeigned a cargoed linear programming model with an objective function of maximizing supplier score. He implemented the model considering 18 suppliers to a manufacturing firm producing agriculture and verbalism equipment. He included cinquer criteria namely quality, supply variety, oral communication, distance and price. In order to maximise the tax function Hong et al. (2005) developed a mixed integer linear model to optimize the occur of suppliers and order quantity. He apply the model to the supply chain of the agriculture industry in Korea as the customer hire varied seasonally over a period of period. Similarly OBrien et al. (2001) created a mixed integer non-linear model to optimize the allocation of products to suppliers so minimizing the annual get costs. Narasimhan et al. (2006) and Wadwa et al. (2007) constructed theoretical multi-objective programming models to optimize supplier selection and order quantity and to minimise lead period, price and way out of rejects. Karpak et al. (1999) constructed a terminal programming model and applied it to an international manufacturing firm to minimise costs and maximise quality and delivery reliability for selection of suppliers and allocation of products between them. The causes considered cost, quality and delivery reliability as the criteria for supplier evaluation.On one hand Mathematical programming is advantageous as compared to the separate approaches as it takes into nib all the constraints during the formulation of the problem. Hence it is much easier to work when a large name of constraints are considered. It can also be used for multiple supplier selection as the current situation can be taken into accounting system in an MP model. On the other hand some of the drawbacks of using an MP model are that it frequently only considers the more tha n quantitative criteria neglecting the qualitative criteria which are classical in supplier selection especially when the goal is to build supplier partnership. just about of the theoretical MP models are complicated to build for the supplier selection problem, due to the large number of variables, but as it can be seen from the above mentioned examples, they can be implemented in an industry as they can be simulated and solved by computers. They are non considered as the most effective method for seller evaluation as they do non take into account qualitative factors and are unequal to(p) of performing a qualitative analysis which is an important aspect of the supplier selection process, thus limiting their use.Data Envelopment Analysis (DEA)The fantasy of DEA is constructed on the basis of calculating the efficiency of the decision alternates or suppliers. The DEA is a non-parametric method the circulars the efficiency without specifying the form of the production function or the weights of different inputs and outputs. The efficiencies are taxd on the basis of benefits as output and cost as the input criteria (DeBoer et al., 2001). The efficiency of a supplier can be be as the ratio of the weighted sum of the suppliers outputs to the weighted sum of his inputs, thus the DEA method manoeuvers the most favourable set of weights for all(prenominal) supplier alternative classifying them into efficient and inefficient suppliers. The favourable set of weights that are calculated maximise the supplier efficiency ratings without altering its own rating or making the other suppliers efficiency ratings more than one (DeBoer et al., 2001).In order to measure the efficiency of alternative suppliers Braglia and Petroni (2000) applied the DEA method by proposing nine evaluating factors to measure the supplier ratings. The actors applied their proposed methodology to the supplier selection process of a middle-sized company manufacturing bottling machinery to t est its efficiency. They also calculated the Cross efficiencies in which the weights elect for a particular supplier can be applied to the weights of the inputs and outputs of the other suppliers as well as Maverick index which is the percentage congener divagation between cross efficiency and open efficiency in order to avoid the selection of false positive supplier. Talluri and Barker (2002) and Talluri and Sarkis (2002) applied DEA to tax suppliers, manufacturers and distributors as a terce phase approach for a logistics distribution crystalizework. They also employed the DEA to measure the performance of the suppliers using six evaluating factors having two inputs and four outputs. Ross et al. (2006) evaluated the supplier performance with respect to the performance attributes of both buyer and supplier by using DEA. The author carried out three sensitivity analysis the first one computed supplier efficiency slews without victorious into account the evaluation teams and the buyers weights. The second analysis considered the evaluation taking into account the teams preferences and the third analysis considered the buyers preference.Liu et al. (2000) constructed a DEA model to evaluate the overall performance of a supplier considering three inputs namely price index, delivery performance and distance factor and two outputs which were supply variety and quality. The authors applied the DEA model to a firm manufacturing agriculture and construction equipment containing a multi modal auxiliary assembly line. The model could select suppliers with a high supply variety, thus reducing the number of suppliers. Seydel et al. (2006) developed a DEA model to evaluate engineering suppliers considering three factors. He included amount of know-how transfer as a qualitative factor in the model. The author developed a five point scale to rank the suppliers in term of the qualitative factor.The DEA method provides a means to evaluate and select suppliers on the ba sis of their performance over a period of time. It compares supplier performance in a multi metre setting thus allowing the purchasing firm to evaluate each suppliers performance sexual intercourse to the performance of the best supplier in the market by calculating the efficiency measures. Observed supplier performance info is used in a DEA method, thus the purchasing firm does non have to calculate its own utility functions as is required in the other techniques. Some of the limitations of the DEA approach are that its focus is not on selection an optimal supplier as the other mathematical programming models hence it cannot be used if the purchasing firm requires the selection of an optimal supplier. The DEA model also makes some assumptions like any other supplier selection model thus limiting its use. (Garfamy et al., 2006)Evolution of the Analytic pecking order Process (AHP)Linear Weighting ModelWeights are assigned to the criteria with the largest weight cor opposeing t o the highest priority, in a linear weighted model. The ratings of the criteria are and then multiplied with their respective weights and the sum of weights is assigned to each supplier, thus the supplier with the highest overall rating can be selected. There are a few imprecisions in the rating mechanism such as obstruction to determine the score of a supplier on a banner or importance of some metre with a high breaker point of precision. To overcome these imprecisions the use of analytic hierarchy process (AHP) was proposed (DeBoer et al., 2001).Analytic Hierarchy ProcessThe AHP is a decision making method first introduced by Saaty (1980) which prioritizes alternatives or suppliers when considering multiple criteria, thus allowing the decision maker to restructure multiplex problems in the form of a set of incorporate directs or a hierarchy. It is one of the most commonly applied methods in practice as it incorporates qualitative as well as quantitative criteria and is rel atively simple to understand. Various adaptations of AHP have been developed since its introduction.Muralidharan et al. (2002) developed an AHP model consisting of five stages to rate and select suppliers considering nine criteria. Some of the major criteria that the author considered were quality, delivery, price and technical foul ability. The model was then applied to the supplier selection process to evaluate six suppliers of a leading organization manufacturing bicycles. Liu and Hai (2005) created an AHP model and used Noguchis voter turnout and ranking system thus allowing each manager to determine the order of criteria kind of of weights for the selection and evaluation of suppliers. They used a six feeling process for supplier evaluation and considered eight criteria in their analysis, some of them be quality, responsiveness, delivery, technical capabilities etc. The authors applied this model for selecting one of ten suppliers for the umbrella Scheme of Malaysias furnit ure industry.Chan and Chan (2004) constructed an AHP model considering six criteria namely cost, delivery, flexibility, innovation, quality and dish out with cardinal sub-factors among them. They applied the model to the supplier selection process of a leading company that manufactures and supplies semiconductor assembly equipment assuming that the supplier had to be chosen for a critical product. The relative priority ratings were calculated based on customer or buyer requirements. Hou et al (2007) developed a decision support system based on AHP in a mass customization environment considering internal and external factors to meet market requirements. The author applied the model to the selection process of a subsidiary company of a local Chinese printer manufacturer. Chan (2003) created an AHP based interactive selection model which determined the relative importance of evaluating criteria without being subjected to human judgment. The AHP model can also be integrated with other supplier selection models in order to achieve optimized selection results.Ramanathan (2007) suggested that the qualitative and quantitative reading gained from the total cost of will power model and AHP model can be utilized to evaluate the performance of a supplier using the DEA method. The author considered the costs from total cost of ownership as inputs and the weights gained from the AHP method as outputs. Sevkle et al. (2007) applied the AHP-DEA integrated method to solve the supplier selection problem of a major Turkish TV manufacturer BEKO, in which he used AHP to derive local weights from a given comparison ground substance and summed up the local weights to get the overall weights. In order to calculate the efficiency scores of all the suppliers DEA was used on the decision making units. Percin (2006) applied integrated AHP-GP method, where AHP was used to measure the priority weightings of alternate suppliers considering twenty evaluating factors. The author used the weightings obtained by AHP Goal programming method as the coefficients for five objective functions. The integrated model was used to optimize the order quantity from the most appropriate supplier considering the capacities of the suppliers.Mendoza et al. (2008) offered an integrated AHP- GP model in order to reduce a large number of potential drop suppliers to a manageable figure. He ranked the alternatives considering five evaluating criteria to optimize the order quantity. Xia and Wu (2007) applied the AHP model to calculate the performance scores of potential suppliers. The authors then applied the scores as coefficients of one of the four objective functions in a multi-objective mixed integer programming model. The model was developed in order to determine the optimal number of suppliers and to select the best set of suppliers.Some of the advantages of AHP method are as follows (Chan et al., 2003)The system can be represented in a hierarchal manner to explain the changes in p riority and its effect at upper and land levels.The desired performance of the supplier is characterized by hierarchical selection criteria viz. the management of the suppliers is wear if the suppliers performance is evident to the buyer.It utilizes multiple paired comparisons of criteria to rank order alternatives and it is the most exceptional Multi- bar decision making approach.Efficiently progresses through modular construction and final assembly of modules than those assembled as a whole, this is known as hierarchical assembly of natural systems.Identifies the key elements assisting in making more broad(a) business decisions and is a structured method which obtains information from target respondents (decision makers or experts).It provides information regarding the structure and function of a system in the lower levels of the hierarchy and gives the outline of the criteria and their purposes in the upper levels. Limitations on the elements in a level are best denoted in th e next higher level to ensure they are satisfied.It has stability and flexibility, stability as small changes have small effects and flexible in the sense that the performance is not hampered if there are any additions to a well structured hierarchyDisadvantages (Chan et al., 2003)Most of the supplier selection problems do not have a single hierarchy.Utilization of this statistical method is complicated for most of the users and this makes the process unmanageable.It is not cost effective to procure the essential information i.e. due to lack of information /willingness to compare two alternatives with respect to some criterion the supposition of comparability is invalid.To reach an agreement with the team members by reviewing the models is time consuming.The presumption that the relative importance of criteria affects the suppliers performance is definite which cannot effectively take into account the risk and skepticism in assessment of suppliers potential performance.Analytic net work process (ANP)Sarkis and Talluri (2000) suggested the use of analytic network process, which was a more sophisticated version of the AHP method. The authors believed that the supplier evaluating factors could influence each other and this interdependence needed to be considered in the process. They applied the ANP process to evaluate and select suppliers in a company manufacturing custom-designed high technology metal-based products, considering organizational factors and strategic performance matrix. The model included seven evaluating criteria namely cost, quality, flexibility, delivery time etc. also considering their interdependencies. Bayazit (2006) implemented an ANP model considering ten evaluating criteria. Some of the important criteria included were on time delivery, quality, flexibility and delivery lead time. He classified the criteria into supplier performance and capabilities practice bundlings and the interdependencies among them were formulated by considering e ach cluster as a controlling factor for a pair sassy comparison matrix.Demirtas and Ustun (2008) developed an integrated model in which they used ANP to evaluate the performance of potential suppliers considering 14 criteria. The weights were then considered in one of the three objective functions of a multi-objective mixed integer programming model. Similarly the authors integrated the ANP and the GP methods of supplier selection and evaluation in 2009. The only difference to the previous model was that there were four goals in the GP model. Gencer et al. (2007) developed ANP model considering various evaluating criteria. He classified them into three clusters to take into account their interrelationships to evaluate and select the most appropriate supplier.Some major advantages of ANP process over AHP are that ANP provides with additional insight as most of the real world supplier selection problems have interdependencies among the evaluating criteria. It also incorporates both q ualitative as well as quantitative factors which are important in supplier selection. The ANP method can deal with various uncertainties and coordination compoundities as it makes use of ratio scales to incorporate a variety of interactions. In spite of the advantages, the ANP method does have a few limitations as it is a very complex method and requires additional effort and time as compared to AHP.Fuzzy fixate TheoryThe wooly-minded set theory is used to model uncertainty and imprecision in the supplier selection situation. Fuzzy set systems make use of linguistic rules which are very well suited to strike the behavior of practical problems. In most of the real world applications, addled rules are created by the decision makers with a few input variables. When the number of input variables increases, the possible number of bleary-eyed rules for a particular system increases exponentially. It is rather difficult for the decision maker to generate a terminate set of rules to assess the supplier selection system (Chan et al., 2006).Chan et al. (2006) presented a hierarchy model based on the fuzzy set theory which could deal with both quantitative and qualitative criteria. The author used linguistic value to assess the ratings and the weights for the evaluation factors. The ratings were arranged in triangular fuzzy numbers. They created a hierarchical structure of the decision problem and applied the model to a high technology manufacturing company to select a suitable supplier to supply material for key components of a new product. Sarkar and Mohapatra (2006) used a fuzzy set method to eliminate the imprecision in a number of subjective characteristics of suppliers. The authors evaluated and selected the suppliers on the basis of performance and capabilities as the two major measures for evaluation. They considered a hypothetical case to exemplify their model by considering a pool of ten suppliers and the goal being to reduce that number and select the b est two suppliers.Kahraman et al. (2003) applied the integrated fuzzy AHP approach to select the most appropriate supplier for the biggest white goods manufacture in Europe to supply the plastic part scroll housing for their new model of aspirators. In this model the decision makers could specify their preferences in term of linguistic variables regarding the priority of each evaluating criteria. Chan and Kumar (2007) also applied a fuzzy AHP methodology for selection of suppliers. The authors used triangular fuzzy numbers and fuzzy synthetic extent analysis methods to choose the final priorities of different criteria. The authors applied the model to the supplier selection process of a manufacturing company to select the best global supplier for one of their critical parts used in the assembling process. The criteria considered in the model for evaluation were overall cost, quality of product, service performance, supplier profile and risk factors.Amid et al. (2006) formulated an integrated fuzzy multi-objective linear programming model which took into account the vagueness and imprecision of the input data in order to optimize the order quantity. The author developed an algorithm to solve the model which incorporated three objective functions with different weights. They considered a hypothetical case to select three suppliers for supplying a new product to a market. The purchasing criteria considered for the model were net price, quality, service and capacity. The author also formulated a fuzzy multi-objective mixed integer programming model which was similar to the earlier model but it also took into account the quantity discount. The price discount was directly proportional to the quantities ordered (Amid et al, 2006).One of the primary advantages of using fuzzy set theory for supplier selection is that it makes use of linguistic variables, which are highly beneficial when the performance values cannot be expresses in terms of means of the numerical val ues. Thus, taking into consideration the uncertainty and imprecision of the quantitative data gathered by the purchasing company or provided by the supplier. It is beneficial and easier to use linguistic variables instead of numerical values while assessing potential suppliers with respect to criteria and weights. A special fuzzy set theory is capable of handling both qualitative as well as quantitative data ratings and is flexible in use, which is an added advantage (Chan et al, 2006). Some of the disadvantages of fuzzy set theory are that the analysis is based on the theory and not exploratory data hence validation of the data may be required. It is a subjective methodology, thus justification for each step is necessary. As the number of variables increase the complexness increases, thus requiring a number of procedures in the sub-systems of the methodology.Other MethodsA number of other methodologies exist for the supplier selection problem such as artificial intelligence and ex pert systems which includes case based reasoning (Choy et al, 2005 2002 Humphreys et al, 2003) and Bayesian belief networks (Kreng et al, 2003). Multi-criteria decision methods which include outranking methods (DeBoer et al, 1998 Dulmin et al, 2003), judgmental modeling (DaSilva et al., 2002 Naude and Lockett, 1993), interpretive geomorphologic modeling (Mandal and Deshmukh, 1994) and categorical methods (Houshyar and Lyth, 1992). Multivariate statistical analysis that incorporates structural equation modeling (Lin et al., 2005 Tracey and Tan, 2001), Factor analysis (Krause et al., 2001 Tracey and Tan, 2001) and confidence interval approach (Muralidharan et al., 2001). conclave decision methods (Han and Ahn, 2005 Mandal and Deshmukh, 1994) and multiple integrated methods also exist for supplier selection. all in all the methods that are utilized for selections of suppliers have their own advantages and disadvantages. No method can be said to be the perfect method which covers all aspects of the entire selection process. Modifications and rises can be made to every method in according to the requirements of the decision makers. The selection process can be ameliorate by integrating different techniques in order to negate the limitations of the techniques taken individually. Considering this procedure, the fuzzy integrated AHP model and the DEA integrated ANN model are relatively the best combination of methods that can be implemented for supplier selection.Supplier Selection CriteriaEvolution of supplier selection criteriaA number of criteria need to be considered for the supplier selection decision making process which makes the selection of suppliers a complicated practice. Since the early 1960s, practitioners and academics have been focusing on the analysis of supplier selection criteria and measurement of supplier performance. Dickson et al, (1966) suggested From the purchasing literature is moderately easy to abstract a list of at least 50 distinct f actors that are presented by various authors as being meaningful to consider in a vendor selection decision?. In his work he carried out a survey to identify the most important criteria required for the selection of suppliers. The author came up with 23 criteria and their relative importance for vendor selection. The following table summarizes the 23 criteria and their level of importance.weber et al. (1991) conducted a similar study on the bases of the 23 criteria identified by Dickson (1966). The authors reviewed and classified 74 related articles appearing between 1966 and 1990. Their study provided a clear indication of the issues concerning selection of suppliers. Both the studies indicated net price, quality, delivery and production facility and capacity as the top 4 criteria for supplier evaluation. These two studies were the primary studies done on supplier selection criteria and were the bases of a number of papers in the forthcoming years.A number of changes at a profound level have taken place in the business environment, including purchasing and procurement since Weber et al.s work in 1991. The basic definitions of Dicksons 23 criteria have undergone change and expansion and new criteria have emerged due to a substantial growth in business and supply chain necessarily. Dickson (1966) define net price as price offered by each vendor including discounts and freight charges. In the development of the net price criteria, the term net price had been replacement by the term cost which includes a number of costs such as fixed cost, inventory costs, ordering costs, supplier costs and costs associated with quality, after-sales and technology (Current and Weber, 1994). The term total cost of ownership has also become important in recent times which include not only the purchasing price but also purchasing related costs (Bhutta et al, 2002).The delivery criterion was defined by Dickson (1966) as the ability of each vendor to meet specified delivery schedule s. The delivery criterion has now been developed to incorporate lead time, cycle time, encumbrance quantity and quality, delivery capacity etc (Karpak et al, 1999). According to Dickson quality was defined as the ability of each vendor to meet quality specifications consistently. The quality criterion has now been extended to include inspections and certain specifications such as the ISO9001 system (Lee et al, 2003)In addition to the evolution and development of the basic criteria a number of new criteria have emerged in literature from various authors. Some of the new criteria are flexibility, which includes process and production flexibility, response to change, responsiveness to customer needs (Ghodsypour et al, 2001), flexibility to change the order and order quantity and ability to respond to fluctuating demand (Verma et al, 1998). A product design and development criterion consists of commitment to continuous improvement, product development and improvement, design capabiliti es and continuous improvement in product and process (Chan et al, 2003). Supplier relationship is another criterion that has gained importance in recent years due to integration of various sections of supply chain. Supplier relationship has two aspects, strategic and tactical. The criterion can be sub divided into 4 sections namely strategic long term relationship, tactical long term relationship, strategic short term relationship and tactical short term relationship. Due to the growth in the businesses, buying firms prefer to integrate the suppliers in their supply chain, thus forming a strategic long term alliance with their supplier