Ingeniería y Gestión Industrial

This study is concerned with the integrity assessment of cracked steam turbine rotor components, made of steel X20Cr13, that operate under cyclic loading. Damage accumulation and growth occurred on the leading edge of turbine blade starting from part-through surface flaws. Tensile tests are performed for assessment of the main mechanical and fracture steel properties: specimens are cut out from critical zones of turbine blade body after a given operating time. The subject for experimental studies is a steel bar of circular cross-section with straight-fronted edge crack. The optical microscope measurement and the COD method are used to monitor crack growth during the tests. An automatic crack propagation simulation on the blade is performed by a coupled approach which, starting from the results of a global finite element method (FEM) analysis, proceeds through the sub modelling of the cracked volume in a DBEM dual boundary element method (DBEM) environment and subsequent propagation analysis.

The lean manufacturing is a popular means of continuous improvement that has reshaped manufacturing processes, practices, and principles globally. Originating from the automobile industry, the approach has been used extensively in the manufacturing sector since the 1990s. Basically, lean manufacturing centered around the philosophy of continuously improving performances by systematically eliminating wastes in the manufacturing floor. Lean thinking was introduced to extend the concept from the manufacturing floor to a business operation level. This paper is intended to provide an overview on the concept of lean thinking, discuss in details the five key principles constituting the concept.

Lifting integer variables is a widely used technique to create strong cutting planes. In 1975, Wolsey introduced a method to compute the exact sequential lifting coefficients of bounded integer variables by solving many integer programs. This paper presents a new technique to perform exact sequentially up and down lifting of general integer variables. The technique requires solving only a single branching tree. Some computational results demonstrate that this new sequential lifting technique performed approximately 11 times faster than Wolsey?s technique.

The concepts of alpha (α) and beta (β) have attained ubiquitous presence in the investment jargon of our times and are the bedrock of Modern Portfolio Theory (MPT) and the Nobel Prize-winning Capital Asset Pricing Model (CAPM). Portfolio managers routinely boast of their superior skills in generating alpha-their excess return relative to their benchmark. Copying the newest fad, hedge funds and proprietary trading desks tack on ‘alpha’ to the name of newfangled funds. Strategies are hawked as “portable alpha” and claimed to be the panacea for outperforming an index. On Main Street, the local postman-turned-investor logs on to Seeking Alpha.com to get the inside tip for the next big “two-bagger”. Alas, few mangers-and even fewer retail investors-have been able to consistently generate this everelusive alpha.

This editorial article presents the bullwhip effect which is one of the major problems faced by supply chain management. The bullwhip effect represents the demand variability amplification as demand information travels upstream in the supply chain. The bullwhip effect research has been attempting to prove its existence, identify its causes, quantify its magnitude and propose mitigation and avoidance solutions. Previous research has relied on different modeling approaches to quantify the bullwhip effect and to investigate the proposed mitigation/avoidance solutions. Extensive research has shown that smoothing replenishment rules and collaboration in supply chain are the most powerful approaches to counteract the bullwhip effect. The objective of this article is to highlight the bullwhip effect avoidance approaches with providing some interesting directions for future research.

The objective of Design for Supply Chain (DFSC) is to design a new product and its corresponding supply chain in a simultaneous manner. Several DFSC models have been developed by previous researchers. However, companies also need to manage the risks associated with both the product design and the supply chain. Many of the previous DFSC models do not consider risk. To determine which risk factors should be included in DFSC models, a survey was developed and administered to industry experts. 29 supply chain risk factors and 21 new product development (NPD) risk factors were included in the survey. This paper shows the process that was used to develop this survey and presents its results. The survey identified a list of the top ten risk factors which includes inventory management/stock out risk, strategic exposure risk, market/demand risks, capacity risks, risk of poor supplier reliability, organizational and project management risks, commercial viability risks, marketing proficiency, supply chain and sourcing risks and financial risks.

In this paper a binary integer linear programming model is proposed for scheduling tour of service personnel in aftersale service process. The model aims to minimize the service personnel’s overall travel time of visiting all customers with additional side conditions that customers should be served by first come first serve (FCFS) priority basis within specified service response time. These side conditions are important strategies in present era of time-based competition. The objective and side conditions are considered for both profitability and effectiveness. Indeed, for given service response time, optimal tour plan would minimize the quantity of service personnel. This decreases the hiring cost of service personnel and thus increases the profitability of after-sale service process. On the other hand, for given quantity of service personnel, optimal tour plan would reduce the service response time. Responsive after-sale service on FCFS priority basis will increase the customer satisfaction, which in turn leads to more repeat orders and hence improves the profitability. The proposed model can capture all realistic constraints of service management process, such as time windows, skill requirement, balanced workload distribution, etc. A numerical illustration is included to demonstrate the effectiveness of the proposed model in conducting economic analysis of an after-sale service process.