Rupy Sawhney

Residential customers elasticity estimation and clustering based on their contribution at incentive based demand response

Incentive-based demand response (IBDR) is an important category of demand response (DR) programs with large untapped potential, especially in the residential sector. Understanding customers elasticity is key to effective design of incentives. However due to limited information, price-based elasticity is needed in IBDR modeling as well. In this work, customer elasticity for an IBDR program is calculated using data from two national surveys and integrated with a detailed residential load model. There are three important aspects about elasticity estimation in this work. First, the elasticity is specific to the structure of the incentives. Second, an elasticity at the individual appliance level in residential sector is more effective for designing incentives than one for aggregate load of the feeder. Third, if elasticity can be classified based on customers contribution and incentive expectations, then targeted incentives can be developed. All of these factors are novel idea for elasticity estimation. Main motivation behind this study is to show necessity of accurate customer modeling for IBDR programs. Distinction between elasticity of each appliance as well as each customer group could lead to huge difference in results of IBDR programs.

Supply chain resilience for single and multiple sourcing in the presence of disruption risks

This paper investigates the use of sourcing strategies to achieve supply chain resilience under disruptions. The coping strategies considered are single and multiple sourcing, backup supplier contracts, spot purchasing, and collaboration and visibility. Collaboration and visibility, which affect suppliers’ recovery capabilities and a buyer’s warning capability, have not been similarly modelled in the past. A scenario-based mathematical model is developed such that it considers objectives under uncertainties including disruption risks and operational risks. A broad numerical study examines its output for various risk attitudes in a decision-maker, ranging from risk neutral to risk averse. The sensitivity of procurement strategies to other key parameters such as recovery and warning capabilities is examined. One of the major findings is that buyer’s warning capability plays a vital role in enhancing supply chain resilience. We seek to build on these efforts to further support disruption planning and mitigation and to obtain a deeper understanding of the relationship between supply chain characteristics and resilience.

Scheduling and route optimisation for labour cost reduction in facility custodial maintenance

Purpose The purpose of this paper is to present an optimised scheduling system for facility mangers and custodians. Experience-driven systems currently in use can result in poor ratings for facility maintenance metrics such as overtime hours, utilisation difference and labour costs. Design/methodology/approach The cleaning schedule and custodian work assignments defined by the manager are simulated for the entire year. Clustering and routing algorithms assign work to custodians equally and find optimal cleaning routes. The manager may use the resulting feedback to iteratively find a suitable schedule which lowers costs. Findings Data were collected at a large university building in consultation with facility management and custodians. Results indicate a significant reduction in overtime hours, improvement in utilisation difference and a lowering of labour costs. Research limitations/implications The methodology was validated at a single building in the facility. Variable selection and optimisation model design will benefit from a comprehensive case study which spans the entire facility. Practical implications The methodology may easily be integrated with existing facility maintenance software, adding to it features such as a manager scheduling interface with feedback on critical cleaning metrics and a custodian user interface which highlights room visitation routes and task times. Originality/value This study acts on the need for facility cleaning labour cost management highlighted in literature. It achieves its goals using a novel combination of scheduling, simulation and optimisation. It is designed to empower key decision-makers, i.e. facility managers and custodians, with better information.

Distribution of load change in industrial demand: A DOE approach

Estimating distribution of load change in response to demand management programs has been targeted in many researches, mostly based on economical and business sale-price models. In this paper a bottom-up analysis approach will be considered. As the first step consumers decision making process has been approximated using mathematical modeling. In this step a novel optimization model for production scheduling will be introduced which takes into account different energy consumption states. In the second step a design of experiment (DOE) model will be developed base on different energy and production factors. In the third step, two new distributions will be introduced based on a variable selected in DOE analysis. The proposed distributions can be obtained based on significant variables and be utilized in market analysis and more specifically, in stochastic analysis.

Production sequencing in a fifth wheel industry: Case study

Fifth wheel is a type of hitch mounted in the bed of a truck. Fifth wheel coupling provides the link between a trailer and the towing truck. Lean methodology is applied to handle production sequencing at fifth wheel industry. Due to high variation of final products and non-constant demand, there is no specific methodology to determine the quantity of production and its order. This results into overproduction and high number of inventory between welding and assembly, and also finished product. We propose a sequencing algorithm between painting and welding area that helps to reduce inventory and movements between welding and assembly. An evaluation is made on the feasibility of coordinating welding production and painting of parts in sequence. The simulation of current and future state indicates shorter lead time and lower work in process.