Dual Coproduct Technologies: Implications for Process Development and Adoption

Published Online:https://doi.org/10.1287/msom.2017.0637

References

  • Bansal S, Transchel S (2014) Managing supply risk for vertically differentiated co-products. Production Oper. Management 23(9):1577–1598.CrossrefGoogle Scholar
  • Bitran G, Gilbert S (1994) Co-production processes with random yields in the semiconductor industry. Oper. Res. 42(3):476–491.LinkGoogle Scholar
  • Bodington CE, Baker TE (1990) A history of mathematical programming in the petroleum industry. Interfaces 20(4):117–127.LinkGoogle Scholar
  • Boyabatlı O (2015) Supply management in multiproduct firms with fixed proportions technology. Management Sci. 61(12):3013–3031.LinkGoogle Scholar
  • Boyabatlı O, Kleindorfer PR, Koontz SR (2011) Integrating long-term and short-term contracting in beef supply chains. Management Sci. 57(10):1771–1787.LinkGoogle Scholar
  • Boyabatlı O, Nguyen DQ, Wang T (2017) Capacity management in agricultural commodity processing and application in the palm industry. Manufacturing Service Oper. Management 19(4):551–567.LinkGoogle Scholar
  • Carrillo JE, Gaimon C (2000) Improving manufacturing performance through process change and knowledge creation. Management Sci. 46(2):265–288.LinkGoogle Scholar
  • CBI (2014) Bayer material science is German industry prize finalist for chlorine production process. Accessed July 26, 2016, http://www.cbi.com/getattachment/98ffdc81-38d3-4906-9099-9114da337f6c/Phenol.aspx.Google Scholar
  • Chen YJ, Tomlin B, Wang Y (2013) Coproduct technologies: Product line design and process innovation. Management Sci. 59(12):2772–2789.LinkGoogle Scholar
  • Cooke M (2010) Combinatrion to unlock high yields and throughout in led production? SemiconductorToday 5(4):110–112.Google Scholar
  • Denton BT, Forrest J, Milne RJ (2006) IBM solves a mixed-integer program to optimize its semiconductor supply chain. Interfaces 36(5):386–399.LinkGoogle Scholar
  • Dong L, Kouvelis P, Wu X (2014) The value of operational flexibility in the presence of input and output price uncertainties with oil refining applications. Management Sci. 60(12):2908–2926.LinkGoogle Scholar
  • Drake DF, Kleindorfer PR, Van Wassenhove LN (2015) Technology choice and capacity portfolios under emissions regulation. Production Oper. Management 25(6):1006–1025.CrossrefGoogle Scholar
  • Ferguson M, Guide Jr VDR, Souza GC (2006) Supply chain coordination for false failure returns. Manufacturing Service Oper. Management 8(4):376–393.LinkGoogle Scholar
  • Fine CH, Porteus EL (1989) Dynamic process improvement. Oper. Res. 37(4):580–591.LinkGoogle Scholar
  • Gerchak Y, Tripathy A, Wang K (1996) Co-production models with random functionality yields. IIE Trans. 28(5):391–403.CrossrefGoogle Scholar
  • Integrated Pollution Prevention and Control (IPPC) (2001) Reference document on best available techniques in the Chlor-Alkali manufacturing industry. Accessed September 17, 2017, https://www.etui.org/content/download/6567/61914/file/chlor-alkali-1.pdf.Google Scholar
  • Katz J (2014) Bayer material science is German industry prize finalist for chlorine production process. Accessed July 26, 2016, http://www.chemicalprocessing.com/industrynews/2014/bayer-material-science-is-german-industry-prize-finalist-for-chlorine-production-process-/.Google Scholar
  • Leachman RC, Benson RF, Liu C, Raar DJ (1996) IMPReSS: An automated production-planning and delivery-quotation system at Harris Corporation—Semiconductor Sector. Interfaces 26(1):6–37.LinkGoogle Scholar
  • Lee D (2012) Turning waste into by-product. Manufacturing Service Oper. Management 14(1):115–127.LinkGoogle Scholar
  • Lee D, Tongarlak M (2017) Converting retail waste into by-product. Eur. J. Oper. Res. 257(3):944–956.CrossrefGoogle Scholar
  • Li G, Rajagopalan S (1998) Process improvement, quality, and learning effects. Management Sci. 44(11-part-1):1517–1532.LinkGoogle Scholar
  • Marcellus RL, Dada M (1991) Interactive process quality improvement. Management Sci. 37(11):1365–1376.LinkGoogle Scholar
  • McKetta J (1990) Encyclopedia of Chemical Processing and Design: Volume 35—Petroleum Fractions Properties to Phosphoric Acid Plants: Alloy Selection, Chemical Processing and Design Encyclopedia (Taylor & Francis, Abington, UK).Google Scholar
  • Millman R (2002) Intel chipping into the speed race. Accessed July 28, 2016, http://www.computing.co.uk/ctg/feature/1824176/intel-chipping-speed-race.Google Scholar
  • Min K, Oren S (1996) Economic determination of specification levels and allocation priorities of semiconductor products. IIE Trans. 27(3):321–331.CrossrefGoogle Scholar
  • Nahmias S, Moinzadeh K (1997) Lot sizing with randomly graded yields. Oper. Res. 47(6):974–986.LinkGoogle Scholar
  • Nexant (2007) Perp program phenol acetone cumene new report alert. Accessed July 26, 2016, http://thinking.nexant.com/sites/default/files/report/field_attachment_abstract/200703/0506_4_abs.pdf.Google Scholar
  • Ng T, Fowler J, Mok I (2012) Robust demand service achievement for the co-production newsvendor. IIE Trans. 44(5):327–341.CrossrefGoogle Scholar
  • Sunar N, Plambeck E (2016) Allocating emissions among co-products: Implications for procurement and climate policy. Manufacturing Service Oper. Management 18(3):414–428.LinkGoogle Scholar
  • Sung JC, Sung M, Sung E (2006) Diamond growth on an array of seeds: The revolution of diamond production. Thin Solid Films 498(1):212–219.CrossrefGoogle Scholar
  • Terwiesch C, Bohn R (2001) Learning and process improvement during production ramp-up. Internat. J. Production Econom. 70(1): 1–19.CrossrefGoogle Scholar
  • Tomlin B, Wang Y (2008) Pricing and operational recourse in coproduction systems. Management Sci. 54(3):522–537.LinkGoogle Scholar
  • Transchel S, Bansal S, Deb M (2016) Managing production of high-tech products with high production quality variability. Internat. J. Production Res. 54(6):1689–1707.CrossrefGoogle Scholar
  • Van Mieghem JA (1998) Investment strategies for flexible resources. Management Sci. 44(8):1071–1078.LinkGoogle Scholar
  • Wang W, Ferguson ME, Hu S, Souza GC (2013) Dynamic capacity investment with two competing technologies. Manufacturing Service Oper. Management 15(4):616–629.LinkGoogle Scholar
  • Zhu Y, Dawande M, Gavirneni S, Jayraman V (2014) Competition and firms’ willingness to implement industrial symbiosis. Working paper, Rider University, Lawrenceville, NJ.Google Scholar
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