F. De Carlo et al. / International Journal of Engineering and Technology (IJET) ISSN : 0975-4024 Vol 5 No 5 Oct-Nov 2013 4312 Service demand forecasting through the systemability model: a case study Filippo De Carlo #1 , Mario Tucci #2 , Orlando Borgia #3 , Nelson Fanciullacci #4 # Department of Industrial Engineering – University of Florence Viale Giovan Battista Morgagni, 40 – 50134 Firenze - Italy 1 filippo.decarlo@unifi.it 2 orlando.borgia@unifi.it 3 mario.tucci@unifi.it 3 nelson.fanciullacci@unifi.it Abstract—Companies competing in an increasingly competitive market must ensure the production of goods with excellent performance, able to satisfy their customers and which have low manufacturing and management costs. It is in this context that companies have, in recent years, invested in research and development and have upgraded their reliability and maintenance functions. In many cases, the maintenance engineers have attempted to predict the reliability of the products, at least for evaluating the number of warranty repairs to be performed. This approach is on the one hand, extremely appropriate but, on the other, must face the difficulties of making laboratory test in conditions often radically different from those that the products meet during their normal operation. Frequently, the reliability estimation, coming from experimental test (in-house) are different from those obtained by the analysis of the service data (in-field). The former are executed in laboratory with standardized, controlled and repeatable conditions, while the latter are affected by random environmental and operating conditions. In the field of household appliances, this is so true that the conditions of use may vary even from country to country. There are some approaches that allow to assess the reliability performance of a system starting from the results of experimental tests performed in a laboratory. One of these was proposed some years ago and is called systemability. In this study, it was applied, for the first time, this approach to the field of household appliances. In addition, we wanted to try to identify the parameters that allowed to distinguish two different European markets. In fact the in-field data come from two different countries and could be considered a great opportunity to validate the correlation model. In fact, it was possible to investigate the effects of two different environmental condition sets (costumer behaviours, , market issues, logistics, etc.) on the reliability performances of a product population that has been manufactured in the same industrial plant. One of the most important outcomes of the Systemability model was the capacity to predicts two different in-field reliability performances relative to two different markets in contrast with the classic methodology that uses the same in-house reliability data without considering environmental effects. The initial stage of modeling was followed by a second validation phase, which gave satisfactory results. The overall outcomes were very positive and they have allowed us to focus some improvements in maintenance management that will lead to greater effectiveness of the method in the coming years. Keyword- Reliability, random environmental factor, Systemability, Availability, Maintainability engineering. I. INTRODUCTION In the last few years, the changes in the global markets have led to an increasing level of competition among companies to be able to satisfy increasingly demanding customers but with fewer economic resources. As a matter of fact the strong integration of international trade business has, on the one hand, significantly increased the number of potential customers but, on the other, the economic recession affecting most of the marketplace is making the business environment more complex and risky. With the diffusion of new media and social network, customers are becoming more sensitive and well informed about the intrinsic characteristics of a product, such as its features, its performances, the level of the after sales services, whether the price is really competitive, and so on. To have a competitive advantage over contenders, manufacturers must focus their attention on those aspects of the product that are tangible for customers as its performances (how well the product accomplishes its functions) and its duration (which is its success probability or, in other words, its reliability). Being able to obtain a high degree of reliability, means that you have to develop a product that, from the earliest design stages, focuses its attention on maintaining the highest level of the quality perceived by the customer, throughout the entire lifecycle. Although reliability estimation requires a large financial commitment, it is indispensable to