The effect of strengthened linear formulations on improving the lower bounds for the part families with precedence constraints problem

The part families with precedence constraints problem (PFP) arises in industry, when flexible manufacturing systems are designed within a group technology approach. The aim of this problem is to arrange parts into families by imposing capacity constraints, concerning both the number of parts and processing times, besides precedence constraints in the building of families.     

Dynamic lot-sizing with setup cost reduction

One of the fundamental tenets of the Just-in-Time (JIT) manufacturing philosophy is that reduction or even elimination of inventory conserves valuable resources and reduces wasteful spending. In many cases, to achieve inventory reductions requires investment in reduction of setup costs. For this reason, certain proposals for incorporating means for reducing setup costs into classical production-inventory models have been offered in recent years. This article considers a dynamic lot-sizing model M where the values of the setup costs can be reduced by various amounts depending upon the level of funds R committed to this reduction. We show that for each fixed value of R, the model can be represented as a shortest path problem. By minimizing the optimal value function V(R) of the shortest path problem over R, model M can, in theory, be solved. In practice, the viability of this approach depends crucially upon the properties of the function V. Since these properties depend upon the nature of the setup cost function K used in model M, we analyze how V varies as K varies. This allows us to propose two exact, finite algorithms for solving model M, one for the case when K is a concave function, the other for the case when K is convex. Computational results for the convex case are presented. The problems solved demonstrate that, in practice, setup cost reductions chosen according to model M have the potential to significantly reduce both inventory levels and total costs.     

Production scheduling with applications in the printing industry

This paper presents a technique for the solution of scheduling problems encountered in a printing company that can be applied to a range of practical industrial problems. The aim of the research was to develop a due date scheduling algorithm within the framework of the scheduling system already in use by the company. The objective was to enable jobs to be scheduled as close to their due dates as possible, while ensuring that the resultant schedule was feasible with respect to work centre capacities and earliest start date constraints.     

Design of manufacturing systems using queueing models

Design issues in various types of manufacturing systems such as flow lines, automatic transfer lines, job shops, flexible machining systems, flexible assembly systems and multiple cell systems are addressed in this paper. Approaches to resolving these design issues of these systems using queueing models are reviewed. In particular, we show how the structural properties that are recently derived for single and multiple stage queueing systems can be used effectively in the solution of certain design optimization problems.Supported in part by the Natural Sciences and Engineering Research Council of Canada via Operating and Strategic Grants on Modeling and Analyses of Production Systems and Modeling and Implementation of Just-in-Time Cells.Supported in part by the NSF Grants ECS-8811234 and DDM-9113008 and by Sloan Foundation Grants for the Consortium for Competitiveness and Cooperation and for the study on Competitive Semiconductor Manufacturing.     

Thermal spraying of composites—Manufacturing and post treatment

Composites are materials with an increasing importance for the industry. A newly developed method for fabrication of fibre-reinforced metal matrix composites permits the production of composites with metal or ceramic fibres by thermal spraying. An improvement of coatings properties and the removal of flaws by post treatment is possible. This paper presents the thermal treatment by laser beam, electron beam and hot isostatic pressing (HIP) process and the mechanical treatment by shot peening.Dedicated to Professor Günther Tölg on the occasion of his 60th birthday     

A new method for solving differential equations with vague parameters

In the literature, it is pointed out that it is better to use vague sets instead of fuzzy sets. Several authors have proposed different methods for solving such differential equations in which all the parameters are represented by fuzzy numbers but to the best of our knowledge till now no one have represented the same as vague sets. In this paper, a new representation of (α, β)-cut, named as JMD (α, β)-cut, is proposed and with the help of JMD (α, β)-cut a new method is proposed to find the analytical solution of vague differential equations. To show the application of proposed method in real life problems the vague Kolmogorov’s differential equations, obtained by using vague Markov model of piston manufacturing system, are solved by proposed method. Also, to show the advantage of JMD (α, β)-cut over existing (α, β)-cut the same vague Kolmogorov’s differential equations are solved by using the proposed method with the help of existing (α, β)-cut and it is shown that the obtained results are not necessarily vague sets while the results, obtained by using JMD (α, β)-cut, are always vague sets.     

A multi-stage stochastic programming approach in master production scheduling

Master Production Schedules (MPS) are widely used in industry, especially within Enterprise Resource Planning (ERP) software. The classical approach for generating MPS assumes infinite capacity, fixed processing times, and a single scenario for demand forecasts. In this paper, we question these assumptions and consider a problem with finite capacity, controllable processing times, and several demand scenarios instead of just one. We use a multi-stage stochastic programming approach in order to come up with the maximum expected profit given the demand scenarios. Controllable processing times enlarge the solution space so that the limited capacity of production resources are utilized more effectively. We propose an effective formulation that enables an extensive computational study. Our computational results clearly indicate that instead of relying on relatively simple heuristic methods, multi-stage stochastic programming can be used effectively to solve MPS problems, and that controllability increases the performance of multi-stage solutions.     

光固化快速成型技术及其应用

本文介绍一种新的制造技术－快速成型制造技术，并且以光固化法为例系统地介绍其原理，构成及特点，给出工业应用的实例。     

Corrosion resistance in chloride solution of the AlSi10Mg alloy obtained by means of LPBF

The paper deals with the corrosion resistance in chloride solutions of an AlSi10Mg alloy obtained by laser powder bed fusion (LPBF) process. The potentiodynamic tests were carried out in solutions having different chloride contents. The results emphasize the role of chloride concentration on localized corrosion. The increase of concentration reduces pitting potential. In addition, the influence of the post-processing heat treatment temperature was recognized. Penetrating attacks occurred either on after low temperatures stress relieving or specimens without any treatment, promoted by selective dissolution of the α-Al phase stimulated by galvanic coupling with noble silicon precipitates at the border of the melt pool. Such penetrating morphology was not observed after heat treatments at high temperature.     

Solar Photooxygenations for the Manufacturing of Fine Chemicals—Technologies and Applications

Photooxygenation reactions involving singlet oxygen (¹O₂) are utilized industrially as a mild and sustainable access to oxygenated products. Due to the usage of organic dyes as photosensitizers, these transformations can be successfully conducted using natural sunlight. Modern solar chemical reactors enable outdoor operations on the demonstration (multigram) to technical (multikilogram) scales and have subsequently been employed for the manufacturing of fine chemicals such as fragrances or biologically active compounds. This review will highlight examples of solar photooxygenations for the manufacturing of industrially relevant target compounds and will discuss current challenges and opportunities of this sustainable methodology.