A sustainable aggregate production planning model for the chemical process industry. (English) Zbl 1391.90219
Summary: Process industries typically involve complex manufacturing operations and thus require adequate decision support for aggregate production planning (APP). In this paper, we focus on two relevant features of APP in process industry operations: (i) sustainable operations planning involving multiple alternative production modes/routings with specific production-related carbon emission and the social dimension of varying operating rates, (ii) integrated campaign planning with the operational level in order to anticipate production mix/volume/routing decisions on campaign lead times and WIP inventories as well as the impact of variability originating from a stochastic manufacturing environment. We focus on the issue of multi-level chemical production processes and highlight the mutual trade-offs along the triple bottom line concerning economic, environmental and social factors. To this end, production-related carbon emission and overtime working hours are considered as externalized factors as well as internalized ones in terms of resulting costs. A hierarchical decision support tool is presented that combines a deterministic linear programming model and an aggregate stochastic queuing network model. The approach is exemplified at a case example from the chemical industry to illustrate managerial insights and methodological benefits of our approach.
Keywords:
sustainable production; aggregate planning; decision support system; queuing networks; chemical process industryReferences:
| [1] | Adonyi, R.; Biros, G.; Holczinger, T.; Friedler, F., Effective scheduling of a large-scale paint production system, J. Clean. Prod., 16, 225-232, (2008) |
| [2] | Almeder, C.; Preusser, M.; Hartl, R. F., Simulation and optimization of supply chains: alternative or complementary approaches?, OR Spectrum, 31, 95-119, (2009) · Zbl 1160.90501 |
| [3] | Arbiza, M. J.; Bonfill, A.; Guillén, G.; Mele, F. D.; Espunã, L. P., Metaheuristic multiobjective optimisation approach for the scheduling of multiproduct batch chemical plants, J. Clean. Prod., 16, 233-244, (2008) |
| [4] | Armbruster, D.; Uzsoy, R., Continuous dynamic models, clearing functions, and discrete-event simulation in aggregate production planning, (Mirchandani, P. B., TutORials in Operations Research: New directions in informatics, optimization, logistics, and production, (2012), INFORMS Hanover), 103-126 |
| [5] | Asmundsson, J.; Rardin, R. L.; Turkseven, C. H.; Uzsoy, R., Production planning with resources subject to congestion, Nav. Res. Logist., 56, 142-157, (2009) · Zbl 1158.90337 |
| [6] | Berlin, J.; Sonesson, U.; Tillmann, A.-M., A life cycle based method to minimise environmental impact of dairy production through product sequencing, J. Clean. Prod., 15, 347-356, (2007) |
| [7] | Berning, G.; Brandenburg, M.; Gürsoy, K.; Kussi, J. S.; Mehta, V.; Tölle, F.-J., Integrated collaborative planning and supply chain optimization for the chemical process industry (i) methodology, Comput. Chem. Eng., 28, 913-927, (2004) |
| [8] | Berning, G.; Brandenburg, M.; Gürsoy, K.; Mehta, V.; Tölle, F.-J., An integrated system solution for supply chain optimization in the chemical process industry, OR Spectrum, 24, 371-401, (2002) · Zbl 1028.90521 |
| [9] | Boukherroub, T.; Ruiz, A.; Guinet, A.; Fondrevelle, J., An integrated approach for sustainable supply chain planning, Comput. Oper. Res., 54, 180-194, (2015) · Zbl 1348.90071 |
| [10] | Brandenburg, M., Low carbon supply chain configuration for a new product a goal programming approach, Int. J. Prod. Res., 53, 6588-6610, (2015) |
| [11] | Brandenburg, M.; Govindan, K.; Sarkis, J.; Seuring, S., Quantitative models for sustainable supply chain management: developments and directions, Eur. J. Oper. Res., 233, 299-312, (2014) · Zbl 1305.90002 |
| [12] | Brandenburg, M., Hahn, G. J. Sustainable aggregate production planning in the chemical process industry - a benchmark problem and dataset. Data Brief Submitted for publication.; Brandenburg, M., Hahn, G. J. Sustainable aggregate production planning in the chemical process industry - a benchmark problem and dataset. Data Brief Submitted for publication. |
| [13] | Brandenburg, M.; Rebs, T., Sustainable supply chain management: a modeling perspective, Ann. Oper. Res., 229, 213-252, (2015) · Zbl 1358.90056 |
| [14] | Brandenburg, M.; Tölle, F.-J., MILP-based campaign scheduling in a specialty chemicals plant: a case study, OR Spectrum, 31, 141-166, (2009) · Zbl 1160.90558 |
| [15] | Burkardt, R.; Hatzl, J., Review, extensions and computational comparison of milp formulations for scheduling of batch processes, Comput. Chem. Eng., 29, 1752-1769, (2005) |
| [16] | Burkardt, R.; Hatzl, J., A complex time based construction heuristic for batch scheduling problems in the chemical industry, Eur. J. Oper. Res., 174, 1162-1183, (2006) · Zbl 1103.90041 |
| [17] | Cefic, 2014. Teaming up for a sustainable europe: the chemical industry’s commitment to sustainability, 2013/2014 report. Brussels, Cefic - The European Chemical Industry Council.; Cefic, 2014. Teaming up for a sustainable europe: the chemical industry’s commitment to sustainability, 2013/2014 report. Brussels, Cefic - The European Chemical Industry Council. |
| [18] | Chakraborty, A.; Malcolma, A.; Colberg, R. D.; Linninger, A. A., Optimal waste reduction and investment planning under uncertainty, Comput. Chem. Eng., 28, 1145-1156, (2004) |
| [19] | Das, K.; Sengupta, S., A hierarchical process industry production-distribution planning model, Int. J. Prod. Econ., 117, 402-419, (2009) |
| [20] | Dietz, A.; Pibouleau, L. G.; Azzaro Pantel, C.; Domenech, S., A framework for multiproduct batch plant design with environmental consideration: application to protein production, Industr. Eng. Chem. Res., 44, 2191-2206, (2005) |
| [21] | Gansterer, M.; Almeder, C.; Hartl, R. F., Simulation-based optimization methods for setting production planning parameters, Int. J. Prod. Econ., 151, 206-213, (2014) |
| [22] | García-Serna, J.; Pérez-Barrigón, L.; Cocero, M., New trends for design towards sustainability in chemical engineering: Green engineering, Chem. Eng. J., 133, 7-30, (2007) |
| [23] | Govindan, K.; Cheng, T., Sustainable supply chain management: advances in operations research perspective, Comput. Oper. Res., 54, 177-179, (2015) |
| [24] | Graves, S. C., A tactical planning model for a job shop, Oper. Res., 34, 522-533, (1986) · Zbl 0609.90061 |
| [25] | (Günther, H.-O.; van Beek, P., Advanced Planning and Scheduling Solutions in Process Industry, (2003), Springer) |
| [26] | (Günther, H.-O.; Meyr, H., Supply Chain Planning - Quantitative Decision Support and Advanced Planning Solutions, (2009), Springer) |
| [27] | Hahn, G.; Packowski, J., A perspective on applications of in-memory analytics in supply chain management, Decis. Support Syst., 76, 45-52, (2015) |
| [28] | Hahn, G. J.; Sens, T.; Decouttere, C.; Vandaele, N. J., A multi-criteria approach to robust outsourcing decision-making in stochastic manufacturing systems, Comput. Industr. Eng., 98, 275-288, (2016) |
| [29] | Mirzapour Al-e hashem, S. M.J.; Baboli, A.; Sazvar, Z., A stochastic aggregate production planning model in a Green supply chain: considering flexible lead times, nonlinear purchase and shortage cost functions, Eur. J. Oper. Res., 230, 26-41, (2013) · Zbl 1317.90051 |
| [30] | Hax, A.; Meal, H., Hierarchical integration of production planning and scheduling, (Geisler, M., Studies in Management Science, (1975), Elsevier), 53-69 · Zbl 0356.90027 |
| [31] | Honkomp, S.; Lombardo, S.; Rosen, O.; Pekny, J., The curse of reality: why process scheduling optimization problems are difficult in practice, Comput. Chem. Eng., 24, 323-328, (2000) |
| [32] | Hugo, A.; Pistikopoulos, E., Environmentally conscious long-range planning and design of supply chain networks, J. Clean. Prod., 13, 1471-1491, (2005) |
| [33] | Ilgin, M. A.; Gupta, S. M., Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art, J. Environ. Manage., 91, 563-591, (2010) |
| [34] | Infante, C. E.D.d. C.; Molica de Mendoça, F.; Purcidonio, P. M.; Valle, R., Triple bottom line analysis of oil and gas industry with multicriteria decision making, J. Clean. Prod., 52, 289-300, (2013) |
| [35] | Ishii, N.; Muraki, M., A process-variability-based online scheduling system in multiproduct batch process, Comput. Chem. Eng., 20, 217-234, (1996) |
| [36] | Jaehn, F., Sustainable operations, Eur. J. Oper. Res., 253, 243-264, (2016) · Zbl 1346.90133 |
| [37] | Jansen, M. M.; de KokTon, G.; Fransoo, J. C., Lead time anticipation in supply chain operations planning, OR Spectrum, 35, 251-290, (2013) · Zbl 1260.90034 |
| [38] | Jawjit, W.; Kroeze, C.; Rattanapan, S., Greenhouse gas emissions from rubber industry in Thailand, J. Clean. Prod., 18, 403-411, (2010) |
| [39] | Jawjit, W.; Pavasant, P.; Kroeze, C., Evaluating environmental performance of concentrated latex production in Thailand, J. Clean. Prod., 98, 8491, (2015) |
| [40] | Jödicke, G.; Zenklusen, O.; Weidenhaupt, A.; Hungerbühler, K., Developing environmentally-sound processes in the chemical industry: a case study on pharmaceutical intermediates, J. Clean. Prod., 7, 159-166, (1999) |
| [41] | Kallrath, J., Combined strategic and operational planning: an milp success story in chemical industry, OR Spectrum, 24, 315-341, (2002) · Zbl 1007.90503 |
| [42] | Kallrath, J., Planning and scheduling in the process industry, OR Spectrum, 24, 219-250, (2002) · Zbl 1007.90506 |
| [43] | Kang, Y.; Albey, E.; Hwang, S.; Uzsoy, R., The impact of lot-sizing in multiple product environments with congestion, J. Manuf. Syst., 33, 436-444, (2014) |
| [44] | Karmarkar, U. S., Lot sizes, lead times and in-process inventories, Manage. Sci., 33, 409-418, (1987) · Zbl 0612.90068 |
| [45] | Kraemer, W.; Langenbach-Belz, M., Approximate formulae for the delay in the queueing system GI/G/1, (1976), International Teletraffic Congress |
| [46] | Lambrecht, M. R.; Ivens, P. L.; Vandaele, N. J., Aclips: a capacity and lead time integrated procedure for scheduling, Manage. Sci., 44, 11, 1548-1561, (1998) · Zbl 0989.90524 |
| [47] | Li, Z.; Ierapetritou, M., Process scheduling under uncertainty: review and challenges, Comput. Chem. Eng., 32, 715-727, (2008) |
| [48] | Linninger, A. A.; Chakraborty, A.; Colberg, R. A., Planning of waste reduction strategies under uncertainty, Comput. Chem. Eng., 24, 1043-1048, (2000) |
| [49] | Méndez, C. A.; Cerdá, J.; Grossmann, I. E.; Harjunkoski, I.; Fahl, M., State-of-the-art review of optimization methods for short-term scheduling of batch processes, Comput. Chem. Eng., 30, 913-946, (2006) |
| [50] | Meyr, H.; Wagner, M.; Rohde, J., Structure of advanced planning systems, (Stadtler, H.; Kilger, C., Supply Chain Management and Advanced PlanningConcepts, Models Software and Case Studies, (2002), Springer), 99-104 |
| [51] | Missbauer, H.; Uzsoy, R., Optimization models of production planning problems, (Kempf, K. G.; Keskinocak, P.; Uzsoy, R., Planning Production and Inventories in the Extended Enterprise, (2011), Springer Boston), 437-507 |
| [52] | Mula, J.; Poler, R.; Garcia-Sabater, J. P.; Lario, F. C., Models for production planning under uncertainty: a review, Int. J. Prod. Econ., 103, 271-285, (2006) |
| [53] | Northrup, H. R.; Wilson, J. T.; Rose, K. M., The twelve-hour shift in the petroleum and chemical industries, Industr. Labor Relat. Rev., 32, 312-326, (1979) |
| [54] | Pahl, J.; Voß, S.; Woodruff, D. L., Production planning with load dependent lead times: an update of research, Ann. Oper. Res., 153, 297-345, (2007) · Zbl 1159.90381 |
| [55] | Papageorgiou, L.; Pantelides, C., A hierarchical approach for campaign planning of multi-purpose batch plants, Comput. Chem. Eng., 17, 27-32, (1993) |
| [56] | Penkuhn, T.; Spengler, T.; Püchert, H.; Rentz, O., Environmental integrated production planning for the ammonia synthesis, Eur. J. Oper. Res., 97, 327-336, (1997) · Zbl 0930.90067 |
| [57] | Rager, M.; Gahm, C.; Denz, F., Energy-oriented scheduling based on evolutionary algorithms, Comput. Oper. Res., 54, 218-231, (2015) · Zbl 1348.90303 |
| [58] | Ribas, I.; Leisten, R.; Framiñan, J., Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective, Comput. Oper. Res., 37, 1439-1454, (2010) · Zbl 1183.90189 |
| [59] | Rutten, W., Hierarchical mathematical programming for operational planning in a process industry, Eur. J. Oper. Res., 64, 363-369, (1993) |
| [60] | Saidur, R.; Mekhilef, S., Energy use, energy savings and emission analysis in the Malaysian rubber producing industries, Appl. Energy, 87, 2746-2758, (2010) |
| [61] | Schneeweiss, C., Distributed decision making: a unified approach, Eur. J. Oper. Res., 150, 237-252, (2003) · Zbl 1137.90562 |
| [62] | Selçuk, B.; Fransoo, J. C.; De Kok, A. G., Work-in-process clearing in supply chain operations planning, IIE Trans., 40, 206-220, (2008) |
| [63] | Seuring, S., A review of modeling approaches for sustainable supply chain management, Decis. Support Syst., 54, 1513-1520, (2013) |
| [64] | Seuring, S.; Müller, M., From a literature review to a conceptual framework for sustainable supply chain management, J. Clean. Prod., 16, 1699-1710, (2008) |
| [65] | Shah, N., Process industry supply chains: advances and challenges, Comput. Chem. Eng., 29, 1225-1235, (2005) |
| [66] | Söhner, V.; Schneeweiss, C., Hierarchically integrated lot size optimization, Eur. J. Oper. Res., 86, 73-90, (1995) · Zbl 0902.90090 |
| [67] | Song, J.; Park, H.; Lee, D.-Y.; Park, S., Scheduling of actual size refinery processes considering environmental impacts with multiobjective optimization, Industr. Eng. Chem. Res., 41, 4794-4806, (2002) |
| [68] | Stadtler, H., Supply chain management and advanced planning - basics, overview and challenges, Eur. J. Oper. Res., 163, 575-588, (2005) · Zbl 1071.90006 |
| [69] | Taticchi, P.; Garengo, P.; Nudurupati, S.; Tonelli, F.; Pasqualino, R., A review of decision-support tools and performance measurement and sustainable supply chain management, Int. J. Prod. Res., 53, 6473-6494, (2015) |
| [70] | Vaklieva-Bancheva, N. G.; Kirilova, E. G., Cleaner manufacture of multipurpose batch chemical and biochemical plants. scheduling and optimal choice of production recipes, J. Clean. Prod., 18, 1300-1310, (2010) |
| [71] | Velez, S.; Maravelias, C. T., Advances in mixed-integer programming methods for chemical production scheduling, Annu. Rev. Chem. Biomol. Eng., 5, 97-121, (2014) |
| [72] | Vogel, M.; Braungardt, T.; Meyer, W.; Schneider, W., The effects of shift work on physical and mental health, J. Neural Transm., 119, 1121-1132, (2012) |
| [73] | Westenberger, H.; Kallrath, J., Formulation of a job shop problem in process industry, Technical Report, (1994), Bayer AG, Leverkusen, Germany and BASF AG, Ludwigshafen, Germany |
| [74] | You, F.; Tao, L.; Graziano, D.; Snyder, S., Optimal design of sustainable cellulosic biofuel supply chains: multiobjective optimization coupled with life cycle assessment and input-output analysis, Am. Inst. Chem. Eng. J., 58, 1157-1180, (2012) |
| [75] | Yue, D.; You, F., Sustainable scheduling of batch processes under economic and environmental criteria with MINLP models and algorithms, Comput. Chem. Eng., 54, 44-59, (2013) |
| [76] | Yura, K., Production scheduling to satisfy workers preferences for days off and overtime under due-date constraints, Int. J. Prod. Econ., 33, 265-270, (1994) |
| [77] | Zhao, Y.; Xu, J.; Xie, X.; Yu, H., An integrated environmental impact assessment of corn-based polyols compared with petroleum-based polyols production, J. Clean. Prod., 68, 272-278, (2014) |
| [78] | Zhou, Z. Y.; Cheng, S. W.; Hua, B., Supply chain optimization of continuous process industries with sustainability considerations, Comput. Chem. Eng., 24, 1151-1158, (2000) |
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