Self Organising Maps for variable selection: Application to human saliva analysed by nuclear magnetic resonance spectroscopy to investigate the effect of an oral healthcare product

SOMs (Self Organising Maps) are derived from the machine learning literature and serve as a valuable method for representing data. In this paper, the use of SOMs as a technique for determining the most significant variables (or markers) in a dataset is described. The method is applied to the NMR spectra of 96 human saliva samples, half of which have been treated with an oral rinse formulation and half of which are controls, and 49 variables consisting of bucketed intensities. In addition, three simulations, two of which consist of the same number of samples and variables as the experimental dataset and a third that contains a much larger number of variables, are described. Two of the simulations contain known discriminatory variables, and the remaining is treated as a null dataset without any specific discriminatory variables added. The described SOM method is contrasted to Partial Least Squares Discriminant Analysis, and a list of the markers determined to be most significant using both approaches was obtained and the differences arising are discussed. A SOM Discrimination Index (SOMDI) is defined, whose magnitude relates to how strongly a variable is considered to be a discriminator. In order to ensure that the model is stable and not dependent on the random starting point of the SOM, one hundred iterations were performed and variables that were consistently of high rank were selected. A variety of approaches for data representation are illustrated, and the main theoretical principles of employing SOMs for determining which variables are most significant are outlined. Software used in this paper was written in-house, allowing greater flexibility over existing packages, and tailored for the specific application in hand.     

Dynamic planned safety stocks in supply networks

Safety stocks are commonly used in inventory management for tactically planning against uncertainty in demand and/or supply. The usual approach is to plan a single safety stock value for the entire planning horizon. More advanced methods allow for dynamically updating this value. We introduce a new line of research in inventory management: the notion of planning time-phased safety stocks. We assert that planning a time-phased set of safety stocks over a planning horizon makes sense because larger safety stocks are appropriate in times of greater uncertainty while lower safety stocks are more appropriate when demand and/or supply are more predictable. Projecting a vector of safety stock values is necessary to assure upstream members in the supply network have advanced warning of changes. We perform an empirical study of U.S. industry, which demonstrates that significant savings can be achieved by employing dynamic planned safety stocks, confirming recent case study reports. We provide a simple optimisation model for the problem of minimising inventory given a vector of safety stock targets. We propose a computationally efficient solution procedure and demonstrate its implementation in an MRP/ERP system. We then illustrate an MRP/ERP planning system feature, which employs a dynamic planned safety stock module that supports a production planner by showing the inventory implications of safety stock plans.     

Simulation based energy-resource efficient manufacturing integrated with in-process virtual management

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow (productivity) and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.     

Schedule instability,service level and cost in a material requirements planning system

The primary objective of this work was to evaluate how four important system parameters (schedule frozen interval, schedule re-planning interval, safety stock and lot-sizing rules) affect material requirements planning (MRP) system performance in terms of schedule instability, total cost and service level, considering different levels of two operating factors: the lead-times of items in the product structure, and the accuracy of the demand forecast. The research design employed a simulation model in Visual Basic run on a personal computer. This study concluded that all system parameters and operating factors significantly influence the three performance measures. Frozen interval, forecast accuracy, and lead-time have the most significant impact on system instability and total cost. Forecast accuracy, safety stock, and lead-time have the most impact on service level. Due to the interactions among system parameters and operating factors, there are no win-win principles to set parameters in order to achieve better system performance under all operating conditions. However, the results help determine appropriate system parameters under particular operating conditions. For example, when the forecast is more accurate, system instability is relatively insensitive to the size of re-planning interval, but frequent re-planning helps reduce total cost and improve service level.     

Weighted tardiness for the single machine scheduling problem:An examination of precedence theorem productivity

Earlier research by Kanet [11] has provided a number of new theorems for deciding precedence between pairs of jobs for 1∣∣Σw_jT_j. The theorems supplant those of Rinnooy Kan, Lageweg, and Lenstra [16]. Presented here are the results of an analysis of the marginal benefit these new theorems provide over the earlier versions of Rinnooy Kan et al. Results show that the new theorems can provide noteworthy improvements in the ability to discover precedence relations between job pairs. For a large set of problem instances the new theorems uncovered up to 8% more precedence relations than the original theorems of Rinnooy Kan et al. The improvement in the productivity in discovering precedence relations shows to be dependent on the coefficient of variation of the distribution of job weights. Logical application of the theorems is to include them in search procedures and/or heuristic approaches to 1||Σw_jT_j. One such heuristic based on the theorems is provided here in which the solutions to a large set of sample problems are within 8–12% of the optimum.     

Investigation on industrial dataspace for advanced machining workshops: enabling machining operations control with domain knowledge and application case studies

Journal of Intelligent Manufacturing - The machining processes on the advanced machining workshop floor are becoming more sophisticated with the interdependent intrinsic processes, generation of...     

Air-gap-enhanced pearlescent effect in periodic stratified bilayers of Perna viridis shell

Pearlescent effect is a unique optical phenomenon originated by an interference of visible light with biomaterial having periodic structure such as pearls, mother-of-pearls, mollusk shells, beetle wings, and butterfly wings. The pearlescent effect exhibits series of vivid colors at a particular spot as an angle of observation is changed. In this paper, the pearlescent effect in Asian green mussel (Perna viridis) shell was investigated. The nacreous layer of the shells is an assembly of stratified bilayers of alternate aragonite calcium carbonate and organic matrix. A consecutive chemical/thermal treatment was employed to remove the organic layer. The enhanced pearlescent effect, indicated by more vivid and brighter colors, was due to a greater refractive index difference within the treated structure as the organic layers were replaced by air gaps of the same thickness. The modified transfer matrix method developed for the stratified bilayers system was employed to verify enhanced pearlescent effect. The results from theoretical simulation corroborated the visual observation as a 4-time full-width-at-half-maximum increment of the reflectance peak, and a broader spectral coverage was achieved after the replacement of organic layers by air gaps.     

A Weighted Modified Due Date Rule for Sequencing to Minimize Weighted Tardiness

Priority dispatching for minimizing job tardiness has been the subject of research investigation for several decades. Minimizing weighted tardiness however has considerably more practical relevance, but for this objective only a few dispatching rules have been advanced and scientifically compared. We introduce here a new rule, which we call Weighted Modified Due Date (WMDD) and test its effectiveness against other competing rules that have been developed for weighted tardiness. The test is accomplished via a simulation study of a simple queueing system and by static problem analysis. The WMDD rule is found to compare favorably to all the rules tested.