According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/118668/Multi-critea decision_24.pdf

Multi-criteria decision making approaches for supplier evaluation and selection: A literature review

Under the umbrella of buzzwords such as “Business Activity Monitoring” (BAM) and “Business Process Intelligence” (BPI) both academic (e.g., EMiT, Little Thumb, InWoLvE, Process Miner, and MinSoN) and commercial tools (e.g., ARIS PPM, HP BPI, and ILOG JViews) have been developed. The goal of these tools is to extract knowledge from event logs (e.g., transaction logs in an ERP system or audit trails in a WFM system), i.e., to do process mining. Unfortunately, tools use different formats for reading/storing log files and present their results in different ways. This makes it difficult to use different tools on the same data set and to compare the mining results. Furthermore, some of these tools implement concepts that can be very useful in the other tools but it is often difficult to combine tools. As a result, researchers working on new process mining techniques are forced to build a mining infrastructure from scratch or test their techniques in an isolated way, disconnected from any practical applications. To overcome these kind of problems, we have developed the ProM framework, i.e., an “pluggable” environment for process mining. The framework is flexible with respect to the input and output format, and is also open enough to allow for the easy reuse of code during the implementation of new process mining ideas. This paper introduces the ProM framework and gives an overview of the plug-ins that have been developed.

/pdf/the-prom-framework-a-new-era-in-process-mining-tool-support-2kr3u2gjvl.pdf

The prom framework: a new era in process mining tool support

Supplier selection and order lot sizing modeling: A review

Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain

Strategic sourcing plays a critical role in supply chain planning. Supplier selection is one of the decisions that determine the long-term viability of a company. In this paper, a new simulation optimization methodology is presented to make decisions on supplier selection. The methodology is composed of three basic modules: A genetic algorithm (GA) optimizer, a discrete-event simulator and a supply chain modelling framework. The GA optimizer continuously search different supplier portfolio and related operation parameters. Corresponding simulation models are automatically created through an object-oriented process. After simulation runs, the fitness value of candidate supplier portfolio is derived from the estimations of key performance indicators (KPI). The fitness is returned to the GA to be utilized in searching the next prominent direction. By using the proposed methodology, the supply chain planner is able to optimize the supplier portfolio with taking uncertainties into consideration. Finally, a rea...

A simulation optimization methodology for supplier selection problem

A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization

This paper addresses the design of production-distribution networks including both supply chain configuration and related operational decisions such as order splitting, transportation allocation and inventory control. The goal is to achieve the best compromise between cost and customer service level. An optimization methodology that combines a multi-objective genetic algorithm (MOGA) and simulation is proposed to optimize not only the structure of the production-distribution network but also its operation strategies and related control parameters. A flexible simulation framework is developed to enable the automatic simulation of the production-distribution network with all possible configurations and all possible control strategies. To illustrate its effectiveness, the proposed method is applied to a real life case study from automotive industry.

Stochastic multi-objective production-distribution network design using simulation-based optimization

The world is becoming more and more a global marketplace and the global environment is forcing companies to take almost everything into consideration at the same time. Increase flexibility is needed to remain competitive and respond to rapidly changing markets. In this context, supplier selection represents one of the most important function to be performed by the purchasin- g department. The supplier selection is a multi-criterion problem which includes both qualitative and quantitative factors (criteria). In order to select the best suppliers it is necessary to make a trade off between these tangible and intangible factors some of which may conflict. This report deals with the 'supplier selection problem', where a state of the art is presented. We summarize the different selection criteria, the various problems of suppliers selection and the existing methods to solve the problem. A numerical example is presented to 1- illustrate the different selection criteria and methods and 2- to compare the advantages and the disadvantage of the selection methods.

https://hal.inria.fr/inria-00071860/document

Supplier Selection Problem : Selection Criteria and Methods

Business process modeling is the basis of business process management. The target of business process modeling is to get an abstract representation of the actual business processes. Although there are many business modeling methods, no well established modeling standard is available in this area. This paper reviews major business process modeling methods. Important aspects of these methods are discussed, including meta-model, graphical notation, serial representation, and tool support.

Hongwei Ding

Papers

A simulation optimization methodology for supplier selection problem

A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization

Stochastic multi-objective production-distribution network design using simulation-based optimization

Supplier Selection Problem : Selection Criteria and Methods

A Comparison of Business Process Modeling Methods