Manufacturing Operations Manuscripts Published in the First 52 Issues of POM: Review, Trends, and Opportunities

Abstract

W e review the manuscripts accepted for publication by the Manufacturing Operations Department of Production and Operations Management (POM) over 13 years (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004). The manuscripts managed by this department deal with topics including scheduling, manufacturing systems management, inventory control and capacity management, maintenance management, and teaching and applications. In the process of this review, we highlight the significant contribution of POM to the field of operations management and illustrate how this body of work has served to further the mission of the journal and department. We then offer comments regarding characterizations of these manuscripts and a few ideas on how to expand this body of work in the future to further the mission of the journal.

Contingency theory of capacity planning: The link between process types and planning methods

“…Some studies have already implied evidence of such an effect (Sheu and Wacker, 2001;Wacker and Sheu, 2006). However, they have not included finite-loading techniques, which is a major shortcoming because substantial effort has been put into their development (Kouvelis et al, 2005). The development of progressive algorithms and software can be well justified if there is evidence on the direct relationship between the sophistication of planning methods and performance.…”

“…Consequently, it is not surprising that planning methods has always been a major research area in the operations management literature. Different planning techniques have been studied, especially in analytical and simulation-based research (Kouvelis et al, 2005). Those streams of research have produced various sophisticated algorithms that enable the leveling and optimization of production plans (e.g., Davis and Mabert, 2000;Yang et al, 2002;Deblaere et al, 2007).…”

Adaptive Production Scheduling and Control in One-Of-A-Kind Production

“…During real production, disturbances are manifested in such occurrences as machine breakdown, operator absence, longer than expected processing times, new emergent orders, and so on (McKay et al, 2002), all of which may fail the original offline schedule and then require online re-scheduling for adaptive production control. Consequently, heuristics based on strong assumptions are not robust, making production scheduling systems inflexible (Kouvelis et al, 2005), and a large gap exists between theoretical research and industrial applications (Gupta & Stafford, 2006;MacCarthy & Liu, 1993).…”

Performance evaluation and capacity planning in a metallurgical job-shop system using open queueing network models

“…Various studies have used parametric decomposition as approximations to evaluate performance measures of queueing networks, such as in Kuehn (1979), Shanthikumar and Buzacott (1981), Albin (1982Albin ( , 1984, Whitt (1983aWhitt ( , 1983bWhitt ( , 1994Whitt ( , 1995, Bitran and Tirupati (1988, 1989a, 1989b, Segal and Whitt (1989), Boxma et al (1990), Kouvelis and Tirupati (1991), Van Vliet and Rinnooy Kan (1991), Buzacott and Shanthikumar (1993), Suri et al (1993), Sarkar (1994a, 1994b), Souza et al (2001Souza et al ( , 2002aSouza et al ( , 2002b, Ketzenberg et al (2003) and Kouvelis et al (2005).…”

“…While insufficient capacity allocation may cause high WIP and long leadtimes, excess of capacity may result in idle resources due to the low levels of machine utilization (traffic intensity). Studies applying job-shop optimization models can be found in, e.g., Tirupati (1989a, 1989b), Boxma et al (1990), Kouvelis and Tirupati (1991), Schweitzer and Seidmann (1991), Van Vliet and Rinnooy Kan (1991), Bitran and Dasu (1992), Calabrese (1992), Sarkar (1994a, 1994b), Frenk et al (1994), Sundarraj et al (1994), Bretthauer (1996), Seshadri and Pinedo (1999), Bitran and Morabito (1999), Shanthikumar and Xu (2000), Souza and Ketzenberg (2002), Souza et al (2002aSouza et al ( , 2002b and Kouvelis et al (2005). For studies dealing with logistics and supply chains using queueing network models, the reader is referred to, e.g., Nakano and Ohno (1999), Warsing et al (2001) and Kerbache and Smith (2004).…”