Logistics and Construction Supply Chains Scott J Mason

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Logistics and Construction Supply Chains Scott J. Mason, Ph. D. Fluor Endowed Chair in

Logistics and Construction Supply Chains Scott J. Mason, Ph. D. Fluor Endowed Chair in Supply Chain Optimization and Logistics Professor of Industrial Engineering

Overview • Construction supply chain management research has focused on one element of the

Overview • Construction supply chain management research has focused on one element of the delivery chain, the contractor • Supply chains should not be viewed from the perspective of a single organization and its ability to control other firms • Necessary to examine all links of the supply chain cutting across organizational and industrial boundaries Scott J. Mason, mason@clemson. edu 2

Builder’s Merchants • Some view the construction supply chain as a pyramid – At

Builder’s Merchants • Some view the construction supply chain as a pyramid – At the apex sits the “major assembler, ” followed by successive tiers of subcontractors • Efficient information sharing ensures the major assembler is supplied with sub-assemblies, materials, and building components by first-tier suppliers – In the United Kingdom, builder’s merchants (BMs) represent the first-tier suppliers linking manufacturers and contractors Scott J. Mason, mason@clemson. edu 3

Two Way Flow • Due to their location in the supply chain, BMs must

Two Way Flow • Due to their location in the supply chain, BMs must manage flow in two directions – Money and information upstream – Materials downstream • In contrast, contractors located at the end of the supply chain only manage upstream flow of money and information • BMs also known as “builders’ bankers” – They bear the cost and risk of holding contingency inventories Scott J. Mason, mason@clemson. edu 4

Construction SCM and Logistics • Construction SCM research tends to focus on strategic interactions

Construction SCM and Logistics • Construction SCM research tends to focus on strategic interactions of businesses – Potential benefits from logistics application have been neglected • “Considerable [waste] is incurred in the [construction] industry as a result of poor logistics” – Based on other industries, some estimate 10%-30% savings can be achieved due to logistics management techniques – Focus must be overall supply chain, not just a single organization/segment • Difficult due to adversarial history? Scott J. Mason, mason@clemson. edu 5

Previous Logistics Studies • Two primary approaches have surfaced 1. Focus on logistics within

Previous Logistics Studies • Two primary approaches have surfaced 1. Focus on logistics within the project environment • • Aim is to improve performance through efficient materials handling and delivery scheduling “Project” logistics management 2. Consider multiple supply chain echelons • • Aim is to improve interactions between suppliers and clients “Supply chain” logistics management • Project approaches dominate the existing literature • This paper focuses on logistics from a supply chain perspective Scott J. Mason, mason@clemson. edu 6

Modeling Challenges Scott J. Mason, mason@clemson. edu 7

Modeling Challenges Scott J. Mason, mason@clemson. edu 7

Why Simulation? • Variability and instability can be dealt with using simulation because it

Why Simulation? • Variability and instability can be dealt with using simulation because it – Investigates operational and structural changes – Explores the interface between parties’ operations and functions – Allows exploration of specific areas of interest – Affords a risk-free (offline) environment Scott J. Mason, mason@clemson. edu 8

Material Delivery Activity Diagram Scott J. Mason, mason@clemson. edu 9

Material Delivery Activity Diagram Scott J. Mason, mason@clemson. edu 9

Additional Inputs of Note • Functional parameters – Multi-drop logic prioritizing where the vehicle

Additional Inputs of Note • Functional parameters – Multi-drop logic prioritizing where the vehicle goes – Reordering policy • Deterministic information – Costs – Fuel price • Stochastic information – Mix of vehicles available – Travel times for vehicles – Demand (based on historical data) Scott J. Mason, mason@clemson. edu 10

Really? • Figure 2 shows a continuous line drawn through discrete experimental points –

Really? • Figure 2 shows a continuous line drawn through discrete experimental points – If a line fit was found, this should be annotated • Two different exponential models were fit with a coefficient of determination R 2=0. 99 – “seem to fit the data very well” • This is beyond the realm of expected goodness! Scott J. Mason, mason@clemson. edu 11

Some Takeaways • While I’m not thrilled with the Y-axis labelling, I do like

Some Takeaways • While I’m not thrilled with the Y-axis labelling, I do like the plot displaying sales, cost, and profit • We didn’t need simulation to find out that “logistics costs are affected [by] changes in demand vehicle fleet size” Scott J. Mason, mason@clemson. edu 12