TUE 11:00 AM Parallel - Operations Management and Supply Chains

Full Report:

Using System Dynamics to Evaluate a Push-Pull Inventory Optimization Strategy for Multi-Tier, Multi-Channel Supply Chains by William Killingworth, Frank Lawrence, Regina Chavez, and Nelson Martin
Demand forecasting is quite challenging, especially for items with long production lead time like certain defence related aviation spare parts. When political developments are uncertain and the future operating environments are unknown, shortages arise from demand volatility as well as supply uncertainties. The government strategizes that, while it improves the ability to meet the unexpected demand, it also minimizes expenditure.

This presentation, a pilot study on a helicopter rotor blade with ten identified long-production lead-time parts, illuminates an innovative strategy approach the government can deploy for improving the availability of spare parts efficiently. Optimization techniques are applied to the inventory management of the government supply chain for the highly valued aviation parts. Inventory Analyst, a commercial inventory optimization software package, was developed and distributed by LogicTools/ILOG. The optimization model strategically places the work-in-progress inventory at specific suppliers, thus creating a push-pull boundary in the manufacturing supply chain. A system dynamics model is used to evaluate the performance of the supply chain over time when the optimal safety stocks are in place. The optimum solutions arrived at may substantially improve supply chain response and supply availability with reduced working capital. Through the use of software and simulation results, it was possible to reduce the production lead time to sixty days from one-hundred-twenty or one-hundred-eighty days, depending on the tiers of the manufacturing supply chain. Further, the results specified significant improvement in the recoverability of the supply chain when subjected to a sudden increase in demand.

Psychological Safety and Group Learning: Cycle-Time Reduction for Collaborative Product Development, by Howard Hao-Chun Chuang
The concept of Collaborative Product Development (CPD) has assumed attractiveness in the last two decades as it relates product development across organizational boundaries. Inter-organizational project teams have real-time access and communicate using collaboration software to share information, access design resources, monitor development progress and control the project. CPD teams have to execute intelligence-oriented tasks and team learning activities that have the potential to create a positive change and to influence team productivity and performance. While empirical evidence shows that the effective use of collaboration software saves much time in communication, its effect on improving the productivity of inter-organizational product development teams has been mixed.

For this presentation, a case-study for a vertical product development partnership at a Taiwanese high-tech electronics company analysing the CPD in a manufacturer-supplier dyad is attempted. The company specializing in the design and manufacturing of thermal fans for electronic products introduced collaboration software to foster vertical product development partnerships with a supplier, a tooling company.

The efficacy of the system dynamics model developed generates insights from reality. The system dynamics inquiry helps inter-organizational project teams understand how cognitive and social factors, such as psychological safety, level of collaboration, and group learning affect the development cycle-time more than do technical factors such as the deployment of collaboration software. The simulation results presented proposed:

  1. The managerial board of CPD teams should encourage increasing the frequency of communication and the amount of review. The higher initial level of psychological safety and of manufacturer-supplier collaboration contributes to cycle-time reduction.
  2. Both the manufacturer and the supplier have to create a safe, supportive, encouraging, and engaging environment to foster productive vertical development partnerships. Leadership skills are necessary to stimulate group learning.  
  3. Manufacturers should build collaborative competence with the supplier, providing a working environment where team members easily establish psychological safety. Without doing so, the higher performance goal may in turn harm group learning, team productivity, and time efficiency.


From Waste to Value - A System Dynamics Model for Strategic Decision Making in Closed-Loop Supply Chains, by Christian Lehr and Peter Milling

Original Equipment Manufacturers (OEMs), due to shortening product lifecycles and legislative regulations, face the challenge of handling products at their end-of-use or end-of-life. Since they are held responsible for obsolete products, waste, they work to manage product return flows and develop strategies for efficiently designing product recovery activities. Companies need to deal with questions arising from activities like collection, inspection, remanufacturing, or materials recycling in closed loop supply chain (CLSC). While process-oriented OEMs deal with decisions on appropriate collection, inspection, and remanufacturing capacities; the product-oriented OEMS extend it to B2B and B2C products.

This presentation (part of an ongoing research project) proposes the use of a system dynamics model as an appropriate method for supporting the strategic decision making in CLSCs. An example was given of a high valued electronic product manufactured for the German automotive industry. Four value recovery strategies have been implemented and tested. As the first option, there is no engagement in any value recovery activities, and the attention of the company is kept solely on the premium market. The second option involves collecting old products, remanufacturing these products, and selling them on a secondary market. A third strategic option lies in the collection of old products without remanufacturing activities; as an alternative the old products could be recycled on a raw materials basis. The fourth option denotes the highest degree of value recovery. It involves remanufacturing and selling remanufactured products on a secondary market as well as recycling old products that are not suited for remanufacturing and feeding recycled raw materials into the original production process. Further, the long-term implications under various environmental scenarios have been tested. Accordingly, effective strategies for the collection and value recovery of these products have to be developed.

The simulation experiments presented show the economic potential of an engagement in value recovery activities and at the same time highlight the high complexity and connectivity inherited with various value recovery processes.

Saroj Koul