Stephan Biller

Dynamic Pricing and the Direct-to-Customer Model in the Automotive Industry

The Internet is changing the automotive industry as the traditional manufacturer and dealer structure faces increased threats from third party e-tailers. Dynamic pricing together with the Direct-to-Customer business model can be used by manufacturers to respond to these challenges. Indeed, by coordinating production and inventory decisions with dynamic pricing, the automotive industry can increase profits and improve supply chain performance. To illustrate these benefits, we discuss a strategy that incorporates pricing, production scheduling, and inventory control under production capacity limits in a multi-period horizon. We show that under concave revenue curves, a greedy algorithm provides the optimal solution, and we describe extensions to the model such as multiple products sharing production capacity. Using computational analysis, we quantify the profit potential and sales variability due to dynamic pricing, and we suggest that it is possible to achieve significant benefit with few price changes.

Managing Flexible Capacity in a Make-to-Order Environment

Flexible capacity has been shown to be very effective to hedge against forecast errors at the investment stage. In a make-to-order environment, this flexibility can also be used to hedge against variability in customer orders in the short term. For that purpose, production levels must be adjusted each period to match current demands, to give priority to the higher margin product, or to satisfy the closest customer. However, this will result in swings in production, inducing larger order variability at upstream suppliers and significantly higher component inventory levels at the manufacturer. Through a stylized two-plant, two-product capacitated manufacturing setting, we show that the performance of the system depends heavily on the allocation mechanism used to assign products to the available capacity. Although managers would be inclined to give priority to higher-margin products or to satisfy customers from their closest production site, these practices lead to greater swings in production, result in higher operational costs, and may reduce profits.

Maintenance Opportunity Planning System

Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. Since the majority of PM tasks requires that equipment be stopped, these tasks can generally only be performed during nonproduction shifts, breaks, or other scheduled downtime. Thus, there is a trade-off between time dedicated to production and time available for preventive maintenance. One approach to mitigate this trade-off is to perform maintenance during scheduled production time by strategically shutting down equipment for short time periods. This research developed a systematic method on when to shut down equipment to do maintenance in an automotive assembly environment. It is called maintenance opportunity. The method incorporated real-time information about production and machine failure conditions. A simulation-based algorithm is developed by utilizing the buffer contents as well as machine starvation and congestion to obtain maintenance opportunities during production time.

Energy Saving Opportunity Analysis of Automotive Serial Production Systems (March 2012)

Conventionally, improving production efficiency, flexibility and responsiveness has been the primary research focus of production management, while energy consumption has received relatively little attention. Energy consumption plays a more and more important role in the manufacturing environment. This is mainly driven by energy cost and environmental concerns. When the energy system becomes complicated and coupled with ongoing production, it is very difficult to hunt the “hidden treasure” which affects the overall benefit of a manufacturing system. This paper provides a systematic method to search for energy saving opportunities and strategies. We start from dynamic production transient analysis and provide quantitative analysis for identifying energy saving opportunity in a system. Furthermore, energy saving strategy is justified through cost analysis for tradeoffs between energy savings and throughput loss. A case study is conducted to demonstrate its potential on energy savings in a multistage manufacturing system.

Transient Analysis of Downtimes and Bottleneck Dynamics in Serial Manufacturing Systems

In manufacturing industry, downtimes have been considered as major impact factors of production performance. However, the real impacts of downtime events and relationships between downtimes and system performance and bottlenecks are not as trivial as it appears. To improve the system performance in real-time and to properly allocate limited resources/efforts to different stations, it is necessary to quantify the impact of each station downtime event on the production throughput of the whole transfer line. A complete characterization of the impact requires a careful investigation of the transients of the line dynamics disturbed by the downtime event. We study in this paper the impact of downtime events on the performance of inhomogeneous serial transfer lines. Our mathematical analysis suggests that the impact of any isolated downtime event is only apparent in the relatively long run when the duration exceeds a certain threshold called opportunity window. We also study the bottleneck phenomenon and its relationship with downtimes and opportunity window. The results are applicable to real-time production control, opportunistic maintenance scheduling, personnel staffing, and downtime cost estimation.

Quality/Quantity Improvement in an Automotive Paint Shop: A Case Study

This paper describes the design and implementation of a continuous improvement project at an automotive paint shop. The development is based on a recently developed improvement methodology for production systems with quality-quantity coupled operations, whereby increasing the probability to complete a job during a cycle time leads to decreasing job quality. The implementation of the first stage of the project resulted in over 9% throughput improvement. The second stage predicts additional improvement of 9.5%.

Bottlenecks in Bernoulli Serial Lines With Rework

The bottleneck (BN) of a production system is a machine with the strongest effect on the systems throughput. In this paper, a method for BN identification in serial lines with rework and Bernoulli machines is developed. The method can be applied using either calculated or measured data on blockages and starvations of the machines. For the case of calculated data, a technique for evaluating performance measures of Bernoulli lines with rework is developed. Along with these quantitative contributions, the paper provides three qualitative results. First, it shows that Bernoulli lines with rework do not observe the property of reversibility. Second, it demonstrates that downstream machines may have a larger effect on the throughput than upstream ones. Third, it demonstrates that BNs may be shifting not only because of changes in machine and buffer parameters but also due to changes in quality of parts produced.

Supervisory Factory Control Based on Real-Time Production Feedback

One key characteristic of any process performance is variability; that is, a process rarely performs consistently over time. The bottleneck is one of the main reasons causing the system variability and fluctuation in production. Short-term production analysis and short-term bottleneck identification are imperative to enable manufacturing operations to optimally respond to dynamic changes in system behavior. However, conventional throughput and bottleneck analysis focus on long-term statistic bottleneck identification, which is usually not applicable to a short-term period. An on-line supervisory control method is introduced to search for short-term production constraints with unknown machine reliability distribution and mitigate those constraints to improve system throughput. The control mechanism uses playback simulation of the real production data to identify the bottleneck station, and control parameters of that station to reach a near balanced production line operation by understanding the bottleneck inertia phenomenon. The results ensure the smooth flow of products on the production line and increase the line’s performance.

Transient analysis of Bernoulli serial lines: performance evaluation and system-theoretic properties

Transient behavior of production systems has significant practical and theoretical implications. However, analytical methods for analysis and control of production systems during transients remain largely unexplored. In the framework of serial production lines with Bernoulli machines and finite buffers, this article develops a mathematical model for transient analysis and derives closed-form expressions for evaluating the production rate, consumption rate, work-in-process, and probabilities of machine starvation and blockage during transients. In addition, a computationally efficient procedure based on recursive aggregation is developed to approximate the transient performance measures with high accuracy. Finally, based on the mathematical model derived, system-theoretic properties of several important system transient characteristics are studied.

Real time production improvement through bottleneck control

Variability is a key characteristic for evaluating the performance of a process. Small variability for a bottleneck machine can generate high production variability. Short-term production analysis and bottleneck identification are imperative for enabling optimal response to dynamic changes within the system. In comparison to the rich and abundant literature available on long-term analysis, only a small section of the literature addresses the dynamic bottleneck control policies, which may be used to maximise sustainable benefits. In this paper, a real time bottleneck control method is introduced to efficiently utilise the finite manufacturing resources and to mitigate the short-term production constraints by using two practical approaches: initial buffer adjustment and maintenance task prioritisation. The objective for real time bottleneck control is to obtain a continuous production improvement towards a balanced-line status to increase the throughput efficiently. The benefits of this method are presented by considering an industrial case study of an automotive assembly line. The results obtained from this case study show significant production improvements as compared to traditional approaches.