Seokgi Lee

A Dynamic Algorithm for Distributed Feedback Control for Manufacturing Production, Capacity, and Maintenance

We propose a dynamic algorithm for distributed feedback control which unifies the functions of production and maintenance scheduling at the shop floor level, and machinery capacity control at the CNC level, which are usually considered in isolation in practice. A continuous-time control theoretic approach is used to model dynamics of these three functions in a unified manner, considering stochastic machine failures and a corresponding maintenance interval. Theories of nonlinear control and discontinuous differential equations are used to analytically predict the system dynamics including the resulting discontinuous dynamics.

Energy-aware feedback control for production scheduling and capacity control

In this paper, we propose an energy-aware feedback control model for production scheduling and capacity control. Specifically, we integrate functions of production scheduling and capacity control, taking into account the costs of energy consumption and machine maintenance varied by production capacity, and the penalty cost imposed by just-in-time production requirements. Continuous control variables are used to adjust the system and the resulting dynamics are modelled. Computational experiments show that interrelated dynamics among these three performance factors are well explained by the proposed controllers, and considerably better energy performance, about 20.0–40.0% improvement, in an energy-aware production compared to a conventional strategy.

Smart logistics: distributed control of green crowdsourced parcel services

This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework’s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.

Determination of Bicycle Handle Diameters considering Hand Anthropometric Data and User Satisfaction

Ergonomic product design considering both anthropometric variability and user preference is required for harmonizing the target users and products. In this study, bicycle handle diameters for three size categories were determined by considering anthropometric variability and preference. To design the bicycle handles, a four-step process was applied: (1) define anthropometric data, (2) develop size chart, (3) define a design equation, and (4) determine design values. In the first step, the 1988 US Army data was chosen as anthropometric data for the design target population. In the second step, to develop a size chart of bicycle handle, hand length and circumference were selected as key dimensions by principal component analysis on six representative hand dimensions. Next, a size chart of three categories (small: 175.5 mm, medium: 186.7 mm, and large: 196.2 mm) were derived by K-means clustering analysis for hand length and circumference. In the third step, the design equation accounting geometrical relationship between the sizes of two key dimensions and diameters of bicycle handle was adopted from a relevant existing research. In the last step, design values (40.9 mm, 43.5mm, and 45.7 mm) for each size category were calculated by inputting the sizes of the key dimensions to the design equation. To evaluate user satisfaction level of the bicycle handles, a user testing of three handle prototypes was conducted for 17 participants with various hand sizes. The test results showed that satisfaction scores for each hand group were significantly higher at the corresponding size category.

Energy-Aware Models for Warehousing Operations

There is a growing need in industries worldwide to become more sustainable and energy efficient. Due to rapid increase in demand of goods, there has been a rise in demand of logistics and operational services. This necessitates needs for a large number of warehouses and distribution centers to satisfy demand. It is imperative that warehouses follow the same sustainable development model practiced in other industries. This paper extends energy efficiency techniques suggested for manufacturing to warehousing. Specifically, warehouses are modeled as M/M/c queues where forklifts are servers and this model is used to evaluate performance of energy control policies. The model is then extended to general distribution queues. Experiments based on real-world data yield results that indicate that for system utilization values between 40% and 100%, as the number of servers in the system increases by a factor of 4, energy consumption increases by a factor of 3.78.

Predictive analytics for delivering prevention services

Logical Analysis of Data (LAD) is applied to prevention research.Real data sets from Baltimore City Public Schools are used for LAD analysis.Data patterns explaining childrens conduct disorder are extracted by LAD.We showed how LAD can reduce the cost of delivering prevention services. Early diagnosis and prevention of problematic behaviors in youth play an important role in reducing treatment costs and decreasing the toll of antisocial behavior. Over the last several years, the science of preventing antisocial behavior in youth has made significant strides, with the development of evidence-based prevention programs (EBP) using randomized clinical trials. In this paper, we use a real case implemented by schools in an urban school district of 80,000 students in a mid-Atlantic state to show how predictive analytics can help to improve the quality of prevention programs and reduce the cost of delivering associated services. Data patterns are extracted from conduct disorder assessments using the Teacher Observation of Classroom Adaptation (TOCA) screening instrument and evaluated using the results of the Diagnostic Interview Schedule for Children (DISC). A mathematical method called Logical Analysis of Data (LAD) is used to analyze data patterns. Experimental results show that up to 91.58% of the cost of administering DISC would be saved by correctly identifying participants without conduct disorder and excluding them from the DISC test.

Distributed Feedback Control for Production, Inventory, and CO2 Emissions in an Assemble-To-Order System

We study continuous variable feedback control of an assemble-to-order system with multiple components and multiple workstations to analyse interrelationships among the production system and corresponding CO2 emissions. The proposed dynamic models are designed by proportional and integral control laws, and represent assembly job arrivals along with the component consumption rates at each workstation for controlling finished-goods assembly schedule, and component production rate for controlling component stock levels, respectively. We also develop the unified feedback control algorithm whose objective is to minimize due date deviation from the customer-requested final assembly due date and component inventory discrepancy in respect to the optimum inventory level, simultaneously. Using numerical simulations, we show how dynamics between the inventory and production systems are interrelated, and resulting CO2 emission variation by the production system.

Simulation-based control for green transportation with high delivery service

Shipping operations are facing increasing pressures for tighter delivery service levels and green transportation, which conflict with each other and requires trade-off between fuel consumption and delivery service. Furthermore, responsiveness to customer demand requires rapid generation of good quality solutions. This paper presents a simulation-based feedback control algorithm for real-time vehicle route planning which considers delivery timeliness and fuel efficiency. The proposed control theoretic algorithm uses feedback from simulation to adjust the planned routes for timeliness and adaptively adjust the vehicle speed within an allowable range to improve fuel efficiency. The formulation results in a multi-variable continuous variable control system with non-linear dynamics. The control algorithm extends prior work in distributed arrival time control, which is used as a basis to derive analytical insights into this computational intractable optimization problem. Performance of the algorithm is evaluated using a simulation model of an industrial distribution center.