CATEGORY: SUPPLY CHAIN MANAGEMENT
PSE2015 - ESCAPE25
12th International Symposium on Process Systems Engineering and 25th European
Symposium on Computer Aided Process Engineering
31 May - 4 June 2015
Copenhagen, Denmark
Processing
Pathway/ Supply Chain Optimization Problems for Emerging Energy Technologies:
Issues and Some Promising Directions
Jay H Lee
Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea
Processing
pathway / supply chain optimization problems for emerging energy technologies
(e.g., renewable energy, carbon capture and utilization) are oftentimes
characterized by a large number of technological options, significant amounts
of uncertainty, and multi-scale nature of decisions. This presentation examines
these characteristics through practical examples and offers some promising
research directions.
The problem of large number of technological options will be first
introduced through the examples of microalgae-based bio-refinery and CO2
capture/conversion. Superstructure based modeling and optimization will be
presented as a tool to investigate the problem at a high level in the presence
of significant technological and economic uncertainties. Then, the presentation
will move onto the issue of coupling between long-term planning decisions like
capital investment and policy and shorter-term decisions like production
capacity operation and logistics. This aspect manifests itself as a large
number of decision variables and constraints complicating solution of the
optimization. The optimization complexity gets greatly amplified when the issue
of uncertainty is added to the problem. We will examine both two stage and
multi-stage problems. Examples of biofuel processing supply chain and energy
portfolio optimization for power generation will be used to bring out the
essential features and complications. For solutions, stochastic programming and
approximate dynamic programming will be introduced.
Full Text Source (Subscription or Fee): http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=0CCYQFjABahUKEwii9bnRq4jHAhUJKogKHWmfB4Y&url=http%3A%2F%2Fwww.kt.dtu.dk%2Fenglish%2F-%2Fmedia%2FInstitutter%2FKemiteknik%2FNyheder%2F2015%2F06%2FBook%2520of%2520Abstracts.ashx%3Fla%3Dda&ei=uPi8VaK5I4nUoATpvp6wCA&usg=AFQjCNGmlli0SUtr-YUXwyHcvaVoRHmeCQ&sig2=Wfm1AZ1H1Y1AqUS1ALn7rw&bvm=bv.99261572,d.cGU
Showing posts with label SUPPLY CHAIN. Show all posts
Showing posts with label SUPPLY CHAIN. Show all posts
Thursday, August 13, 2015
Supply Chain Simulation: Creating Competitive Advantage for DSM
CATEGORY: SUPPLY CHAIN MANAGEMENT
PSE2015 - ESCAPE25
12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering
31 May - 4 June 2015
Copenhagen, Denmark
Supply Chain Simulation: Creating Competitive Advantage for DSM
Dorus van der Linden *, Willem Godlieb, Ruud Barendse
DSM Chemical Technology B.V, Urmonderbaan 22, 6167 RD Geleen, Netherlands
Supply Chain Management and Research are rarely combined in industry. In this presentation authors show that when they are, significant benefits can be obtained. The strategic choices made in supply chain management (SCM) have great impact on cost, inventory and customer service experience warranting a clear effective and optimal strategy and operation. DSM and the markets it operates in are continuously changing, thereby creating increasingly complex and dynamic supply chains, a trend which requires periodic reevaluation of the supply chain strategy.
DSM combines extensive supply chain (design) experience with simulation and optimization. Authors employ a broad supply chain optimization toolset, consisting of modular blocks for advanced forecasting, production- , inventory- and network optimization. All tools can be combined with each other and with the two overarching modules; optimization and sensitivity analysis. Advanced forecasting turns public and private DSM data into quantitative indicators for market price and volume. They show evaluation and validation of existing methods for use in DSM markets, proving their value for use in the industry. Production optimization is used to optimize supply chain cost for operations. Modeling the production process in timing and capacity enables balancing of asset utilization, production cost inventory and customer delivery reliability. Authors show how DSM has developed a method for fast and largely automated model development, based on existing discrete event simulation tools. Network optimization adds the complete warehousing & logistics network to the optimization, determining optimal manufacturing (locations and planning strategy), inventory (locations & target levels) and transport (routing & cost). Initial optimization was and still is being done with existing methods, which after tuning to DSM supply chains have proven to deliver significant results. Next to this, they show how DSM implemented tools for multi echelon, multi product, multi asset production allocation optimization with competition for resources. By being prepared and using a pragmatic approach they were able to establish 10 to 20% increase in perfect order rating, 10 to 20% reduction in supply chain costs and 30 to 50% reduction of inventory at different units over the last 3 years, while at the same time enabling greater competitive advantage by having a more transparent, efficient, flexible and responsive supply chain. DSM will continue its development of Supply Chain optimization tools to retain its competitive advantage in supply chain operations. Two main research topics for DSM are dynamic market simulation based on agent based modeling and further advancements in market prediction based on available large datasets.
Full Text Source (Subscription or Fee): http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=0CCYQFjABahUKEwii9bnRq4jHAhUJKogKHWmfB4Y&url=http%3A%2F%2Fwww.kt.dtu.dk%2Fenglish%2F-%2Fmedia%2FInstitutter%2FKemiteknik%2FNyheder%2F2015%2F06%2FBook%2520of%2520Abstracts.ashx%3Fla%3Dda&ei=uPi8VaK5I4nUoATpvp6wCA&usg=AFQjCNGmlli0SUtr-YUXwyHcvaVoRHmeCQ&sig2=Wfm1AZ1H1Y1AqUS1ALn7rw&bvm=bv.99261572,d.cGU
PSE2015 - ESCAPE25
12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering
31 May - 4 June 2015
Copenhagen, Denmark
Supply Chain Simulation: Creating Competitive Advantage for DSM
Dorus van der Linden *, Willem Godlieb, Ruud Barendse
DSM Chemical Technology B.V, Urmonderbaan 22, 6167 RD Geleen, Netherlands
Supply Chain Management and Research are rarely combined in industry. In this presentation authors show that when they are, significant benefits can be obtained. The strategic choices made in supply chain management (SCM) have great impact on cost, inventory and customer service experience warranting a clear effective and optimal strategy and operation. DSM and the markets it operates in are continuously changing, thereby creating increasingly complex and dynamic supply chains, a trend which requires periodic reevaluation of the supply chain strategy.
DSM combines extensive supply chain (design) experience with simulation and optimization. Authors employ a broad supply chain optimization toolset, consisting of modular blocks for advanced forecasting, production- , inventory- and network optimization. All tools can be combined with each other and with the two overarching modules; optimization and sensitivity analysis. Advanced forecasting turns public and private DSM data into quantitative indicators for market price and volume. They show evaluation and validation of existing methods for use in DSM markets, proving their value for use in the industry. Production optimization is used to optimize supply chain cost for operations. Modeling the production process in timing and capacity enables balancing of asset utilization, production cost inventory and customer delivery reliability. Authors show how DSM has developed a method for fast and largely automated model development, based on existing discrete event simulation tools. Network optimization adds the complete warehousing & logistics network to the optimization, determining optimal manufacturing (locations and planning strategy), inventory (locations & target levels) and transport (routing & cost). Initial optimization was and still is being done with existing methods, which after tuning to DSM supply chains have proven to deliver significant results. Next to this, they show how DSM implemented tools for multi echelon, multi product, multi asset production allocation optimization with competition for resources. By being prepared and using a pragmatic approach they were able to establish 10 to 20% increase in perfect order rating, 10 to 20% reduction in supply chain costs and 30 to 50% reduction of inventory at different units over the last 3 years, while at the same time enabling greater competitive advantage by having a more transparent, efficient, flexible and responsive supply chain. DSM will continue its development of Supply Chain optimization tools to retain its competitive advantage in supply chain operations. Two main research topics for DSM are dynamic market simulation based on agent based modeling and further advancements in market prediction based on available large datasets.
Full Text Source (Subscription or Fee): http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=0CCYQFjABahUKEwii9bnRq4jHAhUJKogKHWmfB4Y&url=http%3A%2F%2Fwww.kt.dtu.dk%2Fenglish%2F-%2Fmedia%2FInstitutter%2FKemiteknik%2FNyheder%2F2015%2F06%2FBook%2520of%2520Abstracts.ashx%3Fla%3Dda&ei=uPi8VaK5I4nUoATpvp6wCA&usg=AFQjCNGmlli0SUtr-YUXwyHcvaVoRHmeCQ&sig2=Wfm1AZ1H1Y1AqUS1ALn7rw&bvm=bv.99261572,d.cGU
Monday, July 29, 2013
Strategic network design of downstream petroleum supply chains: Single versus multi-entity participation
CATEGORY: SUPPLY CHAIN
Chemical Engineering Research and Design, Available online 10 June 2013, In Press, Corrected Proof
Strategic network design of downstream petroleum supply chains: Single versus multi-entity participation
Leão José Fernandes (a, b), Susana Relvas (b), Ana Paula Barbosa-Póvoa(b)
a CLC—Companhia Logística de Combustíveis, EN 366, Km 18, 2050-145, Aveiras de Cima, Portugal
b CEG-IST, Instituto Superior Técnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisboa, Portugal
Abstract
The petroleum supply chain (PSC) requires complex studies for decisions involving various problems, including redesign aimed at optimizing existing distribution networks. Authors discuss a multi-entity, multi-echelon, multi-product and multi-transportation downstream PSC network with shared installations, resource capacities, supply sources and demand requirements.
They construct a deterministic mixed integer linear program (MILP) for strategic design and planning of the downstream PSC network that determines optimal depot locations, capacities, transportation modes, routes and network affectations for long term planning. The MILP maximizes the multi-echelon total profits for the petroleum companies along the supply, refining, distribution and retail stages. They test the MILP with an actual Portuguese PSC network involving production at local refineries and supply from a regional hub.
Full Text Source (Subscription or Fee): http://www.sciencedirect.com/science/article/pii/S0263876213002396
Monday, April 22, 2013
Dynamic Supply Chain Management in Oil and Gas Industry
CATEGORY: SUPPLY CHAIN MANAGEMENT
Proceedings of 3rd Asia-Pacific Business Research Conference, 25 - 26 February 2013, Kuala Lumpur, Malaysia
Dynamic Supply Chain Management in Oil and Gas Industry
Shatina Saad, Zulkifli Mohamed Udin and Norlena Hasnan
Abstract
Supply chain (SC) is a dynamic process that entails constant flow of information, materials and funds across multiple functional areas, within and between chain members in order to meet customer’s needs and to maximise their profit. Such dynamic process requires simultaneous acquisition and continuous re-evaluation of partners, technologies and organizational structures. However, firms may encounter problems related to the dynamic process. But, the more flexible the firms deal with the problems in their engagement of stakeholders, the more likely for them to explore, create, and invest in the dynamic capabilities, hence higher performance level over time. Petroleum companies, in this globalisation era is one of the dynamic supply chain entities which requires dynamic process of capabilities and performance. Due to their high degree of uncertainties circulate through the SC network, as a result petroleum companies require dynamic SC capabilities. Motivated by the complexity of uncertainty in the petroleum companies and its typical characteristic of SC, this study intends to understand the process of dynamic SC management. This study proposes to employ interpretivist paradigm where it would guide towards rigour qualitative methodology. This study will provide rich and thick description of the dynamic of SC where the outcome will contribute to the managerial and theoretical perspective of SC management.
Introduction
The motivation of this study is to understand the environment of dynamic supply chain on oil and gas (O&G) industry in Malaysia by looking into the dynamic supply chain capabilities and dynamic supply chain performance. O&G industry span a large scale in a supply chain, from the strategic to the tactical to the operational level and other various functions in the supply chain network, from the purchasing of the raw materials through the refinery manufacturing to the distribution and sales (Pitty, Li, Adhitya, Srinivasan, & Karimi, 2008; Shah, Li, & Ierapetritou, 2011). Integrated and coordinated decision making across various geographically distributed refinery manufacturing and storage sites also offers additional challenges to refinery operations optimization. While refinery manufacturing facilities management is an integral part of enterprise-wide optimization, transportation logistics and finished product distribution management remain important parts of the O&G supply chain. Hence, this study is to identify and understand the dynamic supply chain capabilities and dynamic supply chain performance as a whole perspective of dynamic supply chain on the O&G industry in Malaysia practices. Specifically, the dynamic supply chain capabilities and dynamic supply chain performance will be discussed in this study are the internal firm’s and external firm’s capabilities and controlled by the environmental uncertainty in the dynamic supply chain of O&G industry. The internal firm’s capabilities representing the focal organization meanwhile the external firm’s capabilities representing the upstream and the downstream organization in the O&G industry.
Free Full Text Source: http://wbiworldconpro.com/uploads/malaysia-conference-2013/management/446-Shatina.pdf
Proceedings of 3rd Asia-Pacific Business Research Conference, 25 - 26 February 2013, Kuala Lumpur, Malaysia
Dynamic Supply Chain Management in Oil and Gas Industry
Shatina Saad, Zulkifli Mohamed Udin and Norlena Hasnan
Abstract
Supply chain (SC) is a dynamic process that entails constant flow of information, materials and funds across multiple functional areas, within and between chain members in order to meet customer’s needs and to maximise their profit. Such dynamic process requires simultaneous acquisition and continuous re-evaluation of partners, technologies and organizational structures. However, firms may encounter problems related to the dynamic process. But, the more flexible the firms deal with the problems in their engagement of stakeholders, the more likely for them to explore, create, and invest in the dynamic capabilities, hence higher performance level over time. Petroleum companies, in this globalisation era is one of the dynamic supply chain entities which requires dynamic process of capabilities and performance. Due to their high degree of uncertainties circulate through the SC network, as a result petroleum companies require dynamic SC capabilities. Motivated by the complexity of uncertainty in the petroleum companies and its typical characteristic of SC, this study intends to understand the process of dynamic SC management. This study proposes to employ interpretivist paradigm where it would guide towards rigour qualitative methodology. This study will provide rich and thick description of the dynamic of SC where the outcome will contribute to the managerial and theoretical perspective of SC management.
Introduction
The motivation of this study is to understand the environment of dynamic supply chain on oil and gas (O&G) industry in Malaysia by looking into the dynamic supply chain capabilities and dynamic supply chain performance. O&G industry span a large scale in a supply chain, from the strategic to the tactical to the operational level and other various functions in the supply chain network, from the purchasing of the raw materials through the refinery manufacturing to the distribution and sales (Pitty, Li, Adhitya, Srinivasan, & Karimi, 2008; Shah, Li, & Ierapetritou, 2011). Integrated and coordinated decision making across various geographically distributed refinery manufacturing and storage sites also offers additional challenges to refinery operations optimization. While refinery manufacturing facilities management is an integral part of enterprise-wide optimization, transportation logistics and finished product distribution management remain important parts of the O&G supply chain. Hence, this study is to identify and understand the dynamic supply chain capabilities and dynamic supply chain performance as a whole perspective of dynamic supply chain on the O&G industry in Malaysia practices. Specifically, the dynamic supply chain capabilities and dynamic supply chain performance will be discussed in this study are the internal firm’s and external firm’s capabilities and controlled by the environmental uncertainty in the dynamic supply chain of O&G industry. The internal firm’s capabilities representing the focal organization meanwhile the external firm’s capabilities representing the upstream and the downstream organization in the O&G industry.
Free Full Text Source: http://wbiworldconpro.com/uploads/malaysia-conference-2013/management/446-Shatina.pdf
Monday, May 21, 2012
Oil Refinery Supply Chain Modelling Using Pipe Transportation Simulator
IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 1, March 2012
Jakub Dyntar, Jan Škvor
Department of Economics and Management, Institute of Chemical Technology Prague, 16628, Czech Republic,
Abstract
PTS is particularly suitable for “what-if” analysis in the crude oil, fuels or gas supply chains where the products are transported among warehouses and refineries through the pipe lines. To discuss the basic functionality of proposed simulator authors employ PTS to simulate a real oil refinery supply chain consisting of 16 warehouses and 3 refineries placed in the Czech Republic and Slovakia. The refineries and warehouses are connected by 21 pipe lines. PTS is used to verify a plan of fuels movements among warehouses and refineries as well as a plan of repairs of certain pipe lines in the selected time period of the length of 30 days.
Free Full Text Source: http://www.ijcsi.org/papers/IJCSI-9-2-1-278-285.pdf
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