Most planning and optimization methods in manufacturing logistics assume centralized or hierarchical decision-making using monolithic models. Motivated by the increasing needs to coordinate diverse decision processes and systems, we investigate an auction-theoretic mechanism for production coordination in a supply chain. Our effort focuses on structural mappings between mathematical decomposition and iterative auction mechanisms wherein agents compete based on their local utilities, announced conflict pricing, and production targets. Building upon the rich literature in optimization and auction-theoretic analysis, we investigate the advantages and limitations of this distributed decision scheme on a large set problem in supply chain production planning. Experimental results show that the proposed auction mechanism provides impressive improvement over the traditional monolithic method without significant degradation to the solution quality.