Energy-saving policies for temperature-controlled production systems with state-dependent setup times and costs

There are numerous practical examples of production systems with servers that require heating in order to process jobs. Such production systems may realize considerable energy savings by temporarily switching off the heater and building up a queue of jobs to be processed later, at the expense of extra queueing costs. In this paper, we optimize this trade-off between energy and queueing costs. We model the production system as an M/G/1 queue with a temperature-controlled server that can only process jobs if a minimum production temperature is satisfied. The time and energy required to heat a server depend on its current temperature, hence the setup times and setup costs for starting production are state dependent. We derive the optimal policy structure for a fluid queue approximation, called a wait-heat-clear policy. Building upon these insights, for the M/G/1 queue we derive exact and approximate costs for various intuitive types of wait-heat-clear policies. Numerical results indicate that the optimal wait-heat-clear policy yields average cost savings of over 40% compared to always keeping the server at the minimum production temperature. Furthermore, an encouraging result for practice is that simple heuristics, depending on the queue length only, have near-optimal performance

Condition-based production and maintenance decisions

Machines used in production facilities deteriorate as a result of load and stress caused by production, and thus they eventually require maintenance to stay in an operating condition. The deterioration rate of a machine typically depends on the production rate, implying that we can control its deterioration, and thereby the maintenance planning, by dynamically adjusting the production rate.The main contribution of this thesis is to integrate the two research fields of production planning and condition-based maintenance. We introduce and explore the benefits of condition-based production and maintenance policies that exploit the relation between production and deterioration to improve the trade-off between the opposing targets of having high production outputs and low maintenance costs.The obtained insights are not only interesting from a theoretical point of view, but are also practically relevant due to the ongoing developments in the fields of sensor equipment and the internet of things. These developments enable operators to remotely monitor the deterioration of equipment and to control its usage in real-time, thereby allowing to implement automated condition-based production policies

Comprehensive characterization of an open source document search engine

This work performs a thorough characterization and analysis of the open source Lucene search library. The article describes in detail the architecture, functionality, and micro-architectural behavior of the search engine, and investigates prominent online document search research issues. In particular, we study how intra-server index partitioning affects the response time and throughput, explore the potential use of low power servers for document search, and examine the sources of performance degradation ands the causes of tail latencies. Some of our main conclusions are the following: (a) intra-server index partitioning can reduce tail latencies but with diminishing benefits as incoming query traffic increases, (b) low power servers given enough partitioning can provide same average and tail response times as conventional high performance servers, (c) index search is a CPU-intensive cache-friendly application, and (d) C-states are the main culprits for performance degradation in document search.Web of Science162art. no. 1

Setting optimal production lot sizes and planned lead times in a job shop

In this research, we model a job shop that produces a set of discrete parts in a make-to-stock setting. The intent of the research is to develop a planning model to determine the optimal tactical policies that minimise the relevant manufacturing costs subject to workload variability and capacity limits. We consider two tactical decisions, namely the production lot size for each part and the planned lead time for each work station. We model the relevant manufacturing costs, entailing production overtime costs and inventory-related costs, as functions of these tactical decisions. We formulate a non-linear optimisation model and implement it in the Excel spreadsheet. We test the model with actual factory data from our research sponsor. The results are consistent with our intuition and demonstrate the potential value from jointly optimising over these tactical policies