Published February 2019 | Version v1
Journal article

A stochastic optimisation model for biomass outsourcing in the cement manufacturing industry with production planning constraints

  • 1. Business School, Newcastle University, 5 Barrack Road, NE1 4SE (United Kingdom)
  • 2. Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, 110016 (India)

Description

Highlights: • Using biomass to replace coal in cement industry is economically viable . • Collect biomass via cement reverse logistics network is cost effective . • Stochastic optimisation model is useful to evaluate biomass outsourcing . • Biomass availability affects biomass outsourcing plan . -- Abstract: It is estimated that 12–15% of total global industrial energy is consumed by the Cement Manufacturing Industry (CMI). To improve environmental sustainability, biomass has been used as an alternative to fossil fuels. There is a comprehensive literature on biomass production and conversion, but little attention has been paid to biomass logistics in the cement industry. We propose the use of cement distribution trucks to collect biomass on their return journeys. Compared with the use of specialist biomass suppliers, the collection of biomass via cement distribution networks has greater uncertainties in delivery times, volume and quality. This is because biomass collection is a secondary activity and is subject to cement order quantities and the random geographical locations of cement customers. To cope with these uncertainties, additional on-site storage and handling equipment is required. This paper proposes a stochastic programming model to measure the cost-effectiveness of collecting biomass using returning cement distribution trucks in comparison with purchasing biomass from specialised biomass suppliers. A numerical experiment based on a real-word dataset was conducted to verify the effectiveness of the developed model.

Additional details

Identifiers

DOI
10.1016/j.energy.2018.11.114;
PII
S0360544218323259;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
169
Journal Page Range
p. 515-526
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55018025
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
AVAILABILITY; BIOMASS; CEMENT INDUSTRY; CEMENTS; COAL; ECONOMIC ANALYSIS; MANUFACTURING; OPTIMIZATION; PLANNING; PROGRAMMING; RANDOMNESS; STOCHASTIC PROCESSES; SUSTAINABILITY
Descriptors DEC
BUILDING MATERIALS; CARBONACEOUS MATERIALS; ECONOMICS; ENERGY SOURCES; FOSSIL FUELS; FUELS; INDUSTRY; MATERIALS; RENEWABLE ENERGY SOURCES

Optional Information

Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.