Sequencing jobs in an engineer-to-order engineering environment

Abstract

Engineer-to-order (ETO) firms produce complex -one of a kind -products and desire shorter lead times as a key component to cost competitiveness. In ETO firms, the engineering process is the largest controllable consumer of lead time. Given that lead time is a function of completion rate and scheduling policy, one critical process is to accurately sequence jobs in front of the engineering function. However, unlike other manufacturing models, such as make-to-stock or make-to-order models, the design for an ETO product is not realized until after the engineering process has been completed. Hence, the only information available does not include data normally required by most sequencing algorithms. Therefore, the problem becomes the determination of an accurate schedule within a complex transactional process for jobs which have not even been designed yet. This paper investigates this topic in the context of the engineering process within the ETO model. Based on research conducted in conjunction with multiple firms, common factors are identified which drive complexity, and a new framework and algorithm are presented for using these factors to sequence jobs. Using discrete event simulation, the performance of this new algorithm is found to be a significant improvement over current industry and published methods.

Organizational factors and technological innovation in products engineered to order for the wind energy market

“…Part of such process is the review of the sales order and the engineering steps themselves. Only when the ETO engineering process is completed, the manufacturing process can itself begin since all the necessary specifications for the product are then available (Grabenstetter and Usher, 2015). Thus, the ETO engineering process is responsible for creating new products.…”

“…Researchers (Angle, 2000;Becheikh et al, 2006;Carayannis and Gonzalez, 2003;Chryssochoidis, 2003;Demirbas et al, 2011;D'Este et al, 2012;Hadjimanolis, 2003;Madrid-Guijarro et al, 2009;Martins and Martins, 2002;Matus et al, 2012;Michie and Sheehan, 2003;Sandberg and Stenroos, 2014;Shi and Wu, 2017;Tidd et al, 2008;Valencia et al, 2010;Valladares et al, 2014;Van De Ven and Chu, 2000) who explore the innovation and the organizational factors that affect it do not consider the specific environment of an ETO product. On the contrary, the researchers (Gosling and Naim, 2009;Grabenstetter and Usher, 2015;Hooshmand et al, 2016;Kristianto et al, 2015;Pacagnella Junior et al, 2014;Sjobakk et al, 2014;Walter and Ries, 1996;Wikner and Rudberg, 2005;Willner et al, 2016) who studied ETO and its specific characteristics did not consider the innovation process. Moreover, Grabenstetter and Usher (2015) claimed that little exists about the ETO environment in the literature.…”

“…On the contrary, the researchers (Gosling and Naim, 2009;Grabenstetter and Usher, 2015;Hooshmand et al, 2016;Kristianto et al, 2015;Pacagnella Junior et al, 2014;Sjobakk et al, 2014;Walter and Ries, 1996;Wikner and Rudberg, 2005;Willner et al, 2016) who studied ETO and its specific characteristics did not consider the innovation process. Moreover, Grabenstetter and Usher (2015) claimed that little exists about the ETO environment in the literature.…”

Hybrid modelling of MTO/ETO manufacturing environments for performance assessment

“…In ETO, product specifications are uncertain, with customers requiring the design of a completely new product (Akinc and Meredith 2015). The engineering process is simultaneously a bottleneck and a core process that is never outsourced (Grabenstetter and Usher 2015). Variability and uncertainty are critical in ETO environments, due the different projects simultaneously carried, with different completion levels and constantly subject to changes (Adrodegari et al 2015).…”

Decision process in one-of-a-kind production

“…They claim that project activities are subject to considerable uncertainty, and have performed a survey where they review the fundamental approaches for scheduling under uncertainty such as reactive scheduling, stochastic project scheduling, fuzzy project scheduling, robust (proactive) scheduling and sensitivity analysis. Grabenstetter and Usher (2015) are looking at sequencing of jobs in an engineer-to-order engineering environment. They present a framework to solve the problem of determination of an accurate schedule within a complex transactional process for jobs which have not been designed.…”