Abstract
Biomass utilisation is identified as a promising solution to minimise society’s dependency on fossil fuels for energy generation. By employing the concept of integrated biorefinery, biomass can be converted into power, heat and value-added products in a sustainable and efficient way. To date, biomass can be converted into a spectrum of products with the availability of various biomass conversion pathways. Due to the substantial amount of potential products and conversion technologies, design of chemical products and processing routes in integrated biorefinery has become more challenging. Furthermore, consumer-driven chemical product design has gained magnificent attention in chemical industry, owing to the shifting of market from commodity products to high-value-added products. As a result, the task of chemical product design that is traditionally dedicated to chemists has nowadays become a multifaceted process that requires collective efforts from various fields. In this work, a framework is proposed to facilitate the decision-making involved in the overall chemical product design and production process by integrating four major organisational units of an enterprise: corporate unit, business unit, research and development (R&D) unit and production unit. The corporate unit is responsible for the enterprise goal line setting for the entire chemical product design and production process, the business unit performs detailed analysis on the existing market, the R&D unit is in charge of the design of chemical product that fulfils the customers’ needs while the production unit produces the chemical product. As a whole, the cooperation between these major organisational units of an enterprise design product that fulfils product needs, determines conversion pathways to produce the product from biomass and identifies product demand and price while fulfilling the enterprise goals. To illustrate the proposed methodology, a case study on the design of dry-cleaning solvent from palm-based biomass is presented.
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Abbreviations
- CAMD :
-
computer-aided molecular design
- EFB :
-
empty fruit bunch
- GC :
-
group contribution
- GHG :
-
greenhouse gas
- GWP :
-
global warming potential
- MILP :
-
mixed-integer linear programming
- MINLP :
-
mixed-integer nonlinear programming
- NLP :
-
nonlinear programming
- NPV :
-
net present value
- A P :
-
price of new chemical product
- A C :
-
price of competitor’s product
- T P :
-
demand of new chemical product
- T C :
-
demand of competitor’s product
- Y :
-
total market size for chemical product
- ρ :
-
parameter for elasticity of substitution
- α :
-
parameter for customers’ awareness
- β :
-
parameter for customers’ preference
- λ P :
-
consumers’ preference function of new product
- λ C :
-
consumers’ preference function of competitor’s product
- V p :
-
target property value for property p
- v L p :
-
lower limit for product target property p
- v U p :
-
upper limit for product target property p
- N i :
-
number of occurrence of first order group of type-i
- M j :
-
number of occurrence of second order group of type-j
- O k :
-
number of occurrence of third order group of type-k
- C i :
-
contribution of the first order group of type-i
- D j :
-
contribution of the second order group of type-j
- E k :
-
contribution of the third order group of type-k
- x i :
-
valence of molecular group i
- g :
-
coefficient for types of molecular group i
- B Bio b :
-
available total flowrate of biomass feedstock b
- Q :
-
biomass conversion pathway
- q′:
-
biomass upgrading pathway respectively
- s :
-
intermediate product pathway q, RIbqs
- s′:
-
final product generated
- R I bqs :
-
conversion rate of biomass conversion pathway q
- R II sq′ s ′ :
-
conversion rate of biomass upgrading pathway q′
- T Inter s :
-
total production rate of intermediate product
- T Prod s′ :
-
total production rate of final product
- logK ow :
-
octanol-water partition coefficient
- δ :
-
Hildebrand solubility
- η :
-
viscosity
- T b :
-
boiling point
- T f :
-
flash point
- logLC 50 :
-
lethal concentration
- GP Total :
-
gross profit
- TAC :
-
total annualised cost
- TACC :
-
total annualised capital cost
- TAOC :
-
total annualised operating cost while
- CRF :
-
capital recovery factor
- G Prod s′ :
-
cost of product s’
- G Bio b :
-
cost of biomass feedstock b
- G Cap bq :
-
capital cost for conversion of biomass b
- G Opr bq :
-
operating costs for conversion of biomass b
- G Cap sq′ :
-
capital cost for conversion of intermediate s
- G Opr sq′ :
-
operating costs for conversion of intermediate s
- EB :
-
incremental environmental burden
- PF P :
-
potency factor for product of a conversion pathway
- PF R :
-
potency factor for reactant of a conversion pathway
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Funding
The financial supports from the Ministry of Education, Malaysia, through LRGS grant (Program code: LRGS/2013/UKM-UNMC/PT/05) and Universiti Tunku Abdul Rahman (UTAR) through UTAR Research Fund (Project Number: IPSR/RMC/UTARRF/2016-C2/N02) are gratefully acknowledged.
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Lai, Y.Y., Yik, K.C.H., Hau, H.P. et al. Enterprise Decision-making Framework for Chemical Product Design in Integrated Biorefineries. Process Integr Optim Sustain 3, 25–42 (2019). https://doi.org/10.1007/s41660-018-0037-2
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DOI: https://doi.org/10.1007/s41660-018-0037-2
Keywords
- Product design
- Integrated biorefinery
- Integrated product and process design
- Decision-making
- Enterprise