###### Abstract  
Manufacturing quality cost optimization is a priority in any manufacturing sector due to quality issues impacting companies' reputations and has financial consequences. Quality costs are composed of tangible and intangible costs, however, only tangible costs used to be analyzed because there is no suitable methodology for measuring intangible costs. In this context, an innovative decision support system is developed with an empirical base, applying Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Lean methodology to reduce all quality costs in an efficient way. In quality departments, perceptions, thoughts, and judgments (intangible costs) are not measured and controlled. This study develops an innovative methodology that allows to address this issue in an effective way. Another major innovation is the application of both multi-criteria methodologies to obtain the best combined result for decision making and the optimization of this result, developing an effort-impact matrix based on Lean manufacturing methodology. This system speeds up the decision-making process and assures its efficiency for quality department applications. Moreover, this decision support system may be applicable to any manufacturing sector.  
decision support system; quality costs optimization; intangible costs; AHP; ANP; Lean methodology +
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to measure, with the same criteria, tangible and intangible qualities. Due to this fact, we decided to apply two multi-criteria analysis processes to measure and control all quality costs (intangible and tangible costs) in manufacturing plants.  
Not only is the concept of applying multi-criteria analysis to quality cost innovative, but also the application of Lean methodology [17; 18; 19; 20; 21] to optimize the results of the two different multi-criteria analyses. This system will offer a disruptive and complete solution that allows to address the issue exposed and facilitates decision making.  
It is not trivial that companies look for cost-efficient solutions and this study is aligned with this approach. Consequently, the study covers cost effectiveness, designing an application based on Lean methodology, an effort-impact matrix, that will prioritize those results that with the lowest effort will have the highest impact for the manufacturer. This decision support system will provide to the steering committee enough information in a timely manner to act on those quality issues with the biggest impact and the lowest effort and cost.  
For the above, the layout of this article is as follows: firstly, data was downloaded from the ERP of a manufacturing company, to obtain the list of parts with incidents during the 2-year warranty period, the financial impact, and number of incidents by part (tangible costs). Additionally, the Delphi method [22] was applied, sending surveys to several stakeholders within the company to identify intangible costs. With the previous information, Analytic Hierarchy Process (AHP) [9; 10; 11; 12; 13; 14; 15; 16] and Analytic Network Process (ANP) [23; 24] were implemented. Each process had their own results. A comparison and complete result analysis was undertaken to grant the most efficient results. Finally, results of multi-criteria analysis were optimized by applying an effort-impact matrix based on Lean methodology to obtain the final result and consequently the most efficient decision in terms of quality improvement and reengineering.