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Production Engineering - Science topic

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My name is Gabriela Ribeiro Alves, and I am currently in the tenth semester of Production Engineering at the Universidade Católica de Petrópolis, attending classes in person.
What are the key metrics you recommend for evaluating the effectiveness of the proposed method in improving supplier control, and how can these metrics be adapted to different industry sectors?
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Abc analysis can use to segregate the supplier base on value or impact to organization
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Contemporary scores or innovations in scientific approaches. Hybrid methodologies, emerging themes and cross-cutting issues?
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I think it is worth paying attention to the issue of decision-making in the production planning process, taking into account forecasting changes occurring on the demand and supply side.
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Minimum Quantity Lubrication (MQL) is a theoretically and practically proven technic. When MQL is adopted in a production sector, for example (any machine tool-Lathe, Milling, Grinding, drilling), what are the challenges faced (Pros and Cons)?
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Adoption of Minimum Quantity Lubrication (MQL) in a production sector, such as machine tools (Lathe, Milling, Grinding, Drilling), presents both advantages and disadvantages.
Pros of MQL include:
  1. Lower cost: MQL uses smaller amounts of lubricant compared to conventional lubrication methods, reducing the cost of lubricant and waste disposal.
  2. Improved tool life: MQL reduces friction and wear on cutting tools, extending their life.
  3. Improved surface finish: MQL produces a cleaner, smoother surface finish on the workpiece.
  4. Increased sustainability: MQL reduces the amount of lubricant and waste, leading to a more sustainable production process.
Cons of MQL include:
  1. Difficulty in controlling the flow rate: The small amount of lubricant used in MQL makes it difficult to control the flow rate, leading to potential inconsistencies in the machining process.
  2. Complex setup: The setup of MQL systems can be complex and may require specialized equipment.
  3. Limited range of applications: MQL may not be suitable for all types of materials or machining processes.
  4. Need for frequent monitoring: The small amount of lubricant used in MQL requires frequent monitoring to ensure that the right amount is being applied.
It is important to consider both the advantages and disadvantages of MQL when deciding whether to adopt this technology in a production sector. An in-depth analysis of the specific machining process and material being used, as well as a thorough evaluation of the available MQL systems, can help determine if MQL is a suitable choice.
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Gentlemen, I am conducting a research in my city on the application of the swot matrix in the largest retail chains, and through this application analyzing the impact of the pandemic on these retailers, could give me some idea of ​​how to cross the matrix, with the purpose of defining strategies more accurate for these businesses.
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The guidance/views/example of a SWOT analysis as per the following papers may further help:
  • Helms, M. M. and Nixon, J. (2010) Exploring SWOT analysis ‐ where are we now? : A review of academic research from the last decade, Journal of Strategy and Management, 3, 3, pp. 215-251.
  • Hill, T. and Westbrook, R. (1997) SWOT analysis: it's time for a product recall, Long range planning, 30, 1, pp. 46-52.
  • Pickton, D. W. and Wright, S. (1998) What's SWOT in strategic analysis?, Strategic change, 7, 2, pp. 101-109.
  • Yu, L. and Huimin, G. (2005) Hotel Reform in China: A SWOT Analysis, Cornell Hotel and Restaurant Administration Quarterly, 46, 2, pp. 153-169.
Furthermore, the following publications may help enhance an understanding of SWOT, namely: “…..we prefer TOWS analysis because it starts with an outside-in perspective, whereas SWOT analysis uses an inside-out perspective. An inside-out perspective tends not to consider customers’ wants or competitors advantages. The TOWS analysis is used because changes occur so rapidly that a particular advantage can be rendered meaningless in a very short space of time. Rapid changes often become treats to a company’s survival, though they could also be viewed as opportunities…..” (Kotler and Kartajaya, 2000, pp. 98-99).
  • Kotler, P. and Kartajaya, H. (2000) Repositioning Asia: From Bubble to Sustainable Economy. Singapore: John Wiley & Sons (Asia) Pte Ltd.
  • Weihrich, H. (1982) The TOWS matrix - A tool for situational analysis, Long range planning, 15, 2, pp. 54-66.
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What modern, computerized information technologies in the field of Industry 4.0 are used to implement improvements in production logistics or other logistics areas, such as distribution logistics, supply logistics, transport logistics, etc.?
Please reply
Best wishes
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In recent years, the improvement of production logistics is carried out by optimizing the processes of managing the supply of raw materials, semi-finished products and prefabricated products to specific stages of the production process in accordance with the concept, e.g. just in time. The improvement of production logistics is also made through the optimization of the consumption of raw materials, energy, etc. as part of the improvement of technological production processes. The aforementioned improvement of technological production processes is carried out by implementing such Industry 4.0 technologies as smart technologies, learning machines, network development engineering, industrial Internet of things, automated machines and robotics, horizontal and vertical data system integration, multi-criteria simulation models, additive manufacturing, etc.
Best regards,
Dariusz Prokopowicz
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What types of restructuring processes are used to implement improvements in production logistics or other logistics areas, such as distribution logistics, supply logistics, transport logistics, etc.?
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The SARS-CoV-2 (Covid-19) coronavirus pandemic, through its impact on economic processes in many production companies, accelerated the development restructuring processes implemented through the implementation of new Industry 4.0 technologies, including the use of smart technology, the Internet of Things, learning machines, robotics, artificial intelligence, cloud computing etc. and improvement of production logistics. Currently, many production companies are creating platforms that enable the implementation of team engineering projects implemented in the form of remote work and with the use of the so-called. digital twins of specific designed production processes, complex product designs, multi-stage technological, manufacturing, production processes, etc.
Regards,
Dariusz Prokopowicz
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I am currently pursuing an MSc in Petroleum Production Engineering. I am required to come up with a Project title and subsequently submit a proposal. As such I would like to make use of this forum by inquiring from experts on a suitable project title based on challenges in the Industry in the area of Production Engineering.
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You can study how more or less relevant to crude oil-derived fuels ... solvents, such as petroleum ether and rubber solvent, are mixtures.
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In daily life single period and multi period inventory system is very necessary things. When the selling period is fixed that is we cant sell things outside that fixed time then it is called may be single period. Lets talk about it what is the actual definition.
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Single period inventory models are used typically for determining the optimal order quantity for a perishable product. The most famous example is the Newsboy (Newsvendor) problem, in which the demand for newspapers for a given day is random, there is a cost of overstocking (unsold papers) and understocking (lost profits). The objective is to minimize the expected daily cost and the decision variable is the number of papers to buy (for reselling). this model is useful for any other item that cannot be stocked to be sold in another period, you have to sell it during the period or it is wasted. Many products fit this category: Christmas trees, Halloween costumes, or any other item that is special day or event themed. Fresh produce and meat can be though of in this category as well.
On the other hand, multi-period models are used for items that can be stocked for long periods of time, and demand in subsequent periods can be satisfied from the inventory. The basic EOQ model is the simplest of these models.
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Productivity is a key aspect of economic growth. However, it is also important to choose what should be produced with the growing importance of taking into account the issue of ecology, care for the protection of the natural environment.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What is the significance of the development of production and the productivity in modern economies?
Please reply
I invite you to the discussion
Thank you very much
Best wishes
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… Clearly, increasing resource productivity is the way to resolve conflicts between future development and heavy resource burdens … The primary requirement for long‐term resource productivity development is increased income levels leading to higher resource productivity …Gan, Y., Zhang, T., Liang, S., Zhao, Z., & Li, N. (2013). How to deal with resource productivity: Relationships between socioeconomic factors and resource productivity. Journal of Industrial Ecology, 17(3), 440-451.
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I am a Petroleum Production Engg MSc student at Robert Gordon University in Aberdeen and I am in the process of selecting a topic for my MSc Engineering Investigation proposal.
I would very much appreciate suggestions of good topics and areas of research relevant to my field.
Thanks!
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Dear Mohiuddin Abdullah, during my MSc thesis I worked on the enhanced oil recovery (EOR) via polymer flooding. Due to the increasing demand on fossil energy sources, these EOR techniques such as CO2 injection for pressure restoration and others are still attracting research and field applications. So my suggestion targets on this area of research. My Regards
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I want to find the rotation per unit length of a thin tube using their stress-strain characteristics in incremental theory.
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Stress= Force/ Area
So, Force=Stress* Area
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Torque= Force* Perpendicular distance
So, Torque= Stress* Area * Perpendicular distance
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For example, For a long cylinder of Radius R rotates in a large container of liquid, torque is (2*omega*mu)*(2*Pi*R*L)*R
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To improve the surface integrity of the material.
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Speed of rotation ,feed and depth of cut.
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I wish to create spring elements on each and every mesh node. In this case my element size are 0.08415m and therefore I wish to create every single individual spring along 16.83m pipe length with the distance between springs of 0.08415m. The figure I attached are springs I created by manually input each location of every single spring. I wonder what are the faster ways to create the spring automatically along the 16.83m without having to do it manually? I wish to have it done automatically as I will be reusing the model with different pipe diameter and pipe length and having to remodel every single spring is going kill off a lot of time. I have tried object generator but failed to generate those springs.  Appreciate any help!
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Create entire sketch in modeling software and import it to Ansys Workbench.
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Do the shortening of life cycles of technical products, electronics, household appliances, IT equipment, etc. used by producers is a solution to the potential problem of overproduction?
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No, This will create more overproduction.
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MICLASS and DCLASS coding system in group technology follow which type of coding: monocode, polycode or mixcode? Why Opitz classification and coding system is a mixed code. I can understand that there is the feature of polycode, but I cannot find any feature of monocode or hierarchical order in Opitz coding system.
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Sorry for the very very late answer (I saw this question now only).
This article has list of references that answer your question "Feature extraction from STEP (ISO 10303) CAD drawing files for metalforming process selection in an integrated design system"
The article is available on researchgate
please refer the references listed in it
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Hello Everyone,
I have completed may Bachelors in Industrial & Production Engineering, majoring in Manufacturing Engineering and I am looking for PhD position at USA specially in area of Metal Additive Manufacturing and FDM of cellular structures. Please suggest me good Labs and professors in USA who are working this area.
Thanks,
Sumit
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UTEP, Carnegie Melon, Worchester, Penn State, Texas Tech, UT Austin...Many schools have additive manufacturing facilities. Please check US news engineering grad school ranking and go to each dept. Check ME, IE, ISE and Materials Engineering Dept! Good luck!
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Research strategies in many institutions require to carefully investigating the future trends in disciplines. Other plans such as hiring researchers, establishing new labs, … are based on the how we look to the future of research and our understanding what others working in. I hope that researchers discuss this important issue and exchange the related experiences and knowledge.
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Artificial Intelligence (AI), operations research (OR) and modelling, supply chain (SC), robotics and renewable energy (RE).
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Production Engineering is an Engineering area that deals with the problems of productive operations, with emphasis on the production of goods and services. Operational Research (OR) is defined as the area responsible for solving real problems, using decision-making situations, using mathematical models. The OR is an applied science focused on solving real problems that seeks to apply knowledge from other disciplines such as mathematics, statistics, computation to improve rationality in decision making processes.
Operational Research (OR), responsible for solving real problems, through mathematical and statistical models. How have we used OR in our Searches?
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Dear Leopoldino
I guess that you are referring to OR (Operational Research) and you use the Brasilian OP (Pesquisa Operacional). If it is so, I believe that the most important aspect of your remark is that OR, and most especially Linear Programming (LP) solves real problems, which is possible because its algebraic structure of inequalities. It allows the construction of a scenario model by far much more representative than in any MCDM methods.
LP was developed in 1939 by Leonid Kantarovich, and for this development he was awarded in 1952 the Nobel Prize in Economy. It is then the granddad of all present-day methods for MCDM.
The actual algorithm, the Simplex, is due to the genius of George Dantzing which developed it in 1948. This same algorithm is still used to day, after 70 years, and is, according to some sources, used by about 70,000 large companies world-wide.
LP processes large amounts of information, it is irrelevant the number of alternatives and criteria, which can be in the thousands each, and it is so important, that Excel incorporated it as an add-in since 1991.
However, LP has two severe drawbacks; one of them is that it works with only one objective and with only quantitative criteria, which is not very realistic in nowadays projects. Nowadays, these two problems have been superseded by new methods and software based on LP, which do not yield an optimal solution, as the original Simplex, but one which is probably very close to it.
What is important is that LP allows for modelling very complex scenarios, incorporating features than none of the more than two dozen MCDM in the market can handle, and for this reason, it is able to model real problems, by establishing restrictions, dependencies and even correlation.
In addition, it does not produce Rank Reversal.
I have been using LP for decades and in the late 70s was fortunate enough to act as a counterpart of the Massachusetts Institute of Technology (MIT), to solve by LP in a two years project, a very complex problem related with a river basin.
Since then, I solved more than one hundred problems in very different areas, and many of them have been published in my books, and at present, I am trying to promote its use in RG, where, as you properly say, rationality is paramount.
LP mathematics is a little complex, however, a user does not need to know it, in the same way as he does not need to know the mathematics of AHP, PROMETHHE or TOPSIS. As matter of fact, LP is easier to use than other methods since no weights are needed.
A couple of weeks ago I proposed in RG to develop a course on LP, however, nobody was interested.
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Can advanced data processing in the cloud, Big Data database systems and Business Intelligence analytical platforms be helpful in the processes of restructuring and improving logistics of the functioning of production processes?
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Notably, the significance of supply chain management and and the ways by which it will facilitate and improve production processes is known to those involved in modern industrial enterprises. This requires much IT investment which in turn depends on managing and maintaining big data. In point of fact, large data sets are required to analyze computationally to reveal patterns, trends, and associations which may shed light on logistics management and production engineering . However, promoting sustainable development simply encourages technological advances that are a threat to the earth's resources. As such, the use of big data analysis and interpretation should aim at enhancing Green Logistics in order to help the effective functioning of production processes.
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Suppose in a three layer supply chain there are three different profit function TPs, TPm, TPr then total integrated profit is TIP=TPs+TPm+TPr, if we put TPs=0 then is it reduce to two layer supply chain or not?
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Yeah I mean Supply Chain Management prof. Bruno Durand
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There are lots of Optimization method /Evolutionary algorithms (EAs) in literature. Some of them is more effective (for solving linear/nonlinear problem) compared to other. But we don’t know which will fit our model. As a result we checked for everything as we can do. But cant get the desire result. Some of those methods are 1. Genetic algorithms (GA) ; Haupt and Haupt (2004) 2. Pattern search (Mathlab) 3. Particle swarm optimization (PSO), Binary Particle Swarm Optimization (BPSO); Eberhart and Kennedy (1995) 4. Bee optimization; Karaboga and Bosturk (2007) Pham et al (2006) 5. Cuckoo algorithm; Yang and Deb (2009, 2010) 6. Differential evolution (DE) ; Storn and Price (1995, 1997) 7. Firefly optimization; Yang (2010) 8. Bacterial foraging optimization; Kim, Abraham and Cho (2007) 9. Ant colony optimization (ACO) ; I Dorigo and Stutzle (2004) 10. Fish optimization; Huang and Zhou (2008) 11.Raindrop optimization ; Shah-Hosseini (2009) 12.Simulated annealing ; Kirkpatrick, Gelatt and Vecchi (1983) 13.Biogeography-based optimization (BBO), 14. Chemical reaction optimization (CRO) 15. A group search optimizer (GSO), 16. Imperialist algorithm 17. Swine flow Optimization Algorithm. 18. Teaching Learning Based Optimization (TLBO) 19. Bayesian Optimization Algorithms (BOA) 20. Population-based incremental learning (PBIL) 21. Evolution strategy with covariance matrix adaptation (CMA-ES) 22. Charged system search Optimization Algorithm 23. Continuous scatter search (CSS) Optimization Algorithm 24. Tabu search Continuous Optimization 25. Evolutionary programming 26. League championship algorithm 27. Harmony search Optimization algorithm 28. Gravitational search algorithm Optimization 29. Evolution strategies Optimization 30. Firework algorithm, Ying Tan, 2010 31. Big-bang big-crunch Optimization algorithm, OK Erol, 2006 32. Artificial bee colony optimization (ABC), Karaboga,2005 33. Backtracking Search Optimization algorithm (BSA) 34. Differential Search Algorithm (DSA) (A modernized particle swarm optimization algorithm) 35. Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) 36. Multi-objective bat algorithm(MOBA) Binary Bat Algorithm (BBA) 37. Flower Pollination Algorithm 38. The Wind Driven Optimization (WDO) algorithm 39. Grey Wolf Optimizer (GWO) 40. Generative Algorithms 41. Hybrid Differential Evolution Algorithm With Adaptive Crossover Mechanism 42.Lloyd's Algorithm 43.One Rank Cuckoo Search (ORCS) algorithm: An improved cuckoo search optimization algorithm 44. Huffman Algorithm 45. Active-Set Algorithm (ASA) 46. Random Search Algorithm 47. Alternating Conditional Expectation algorithm (ACE) 48. Normalized Normal Constraint (NNC) algorithm 49. Artificial immune system optimization; Cutello and Nicosia (2002) 50. fmincon .
Besides this there are many other optimization algorithm recently invented which are generally called Hybrid optimization Technique because it’s a combination of two method. If we share our experiences then it will be helpful for all of us who are in the field of optimization. I may be missing some methods, researcher are requested to add those algorithms and the way of use like many model needs initial value, weight, velocity, different type of writing objective function etc. I am facing some problems that’s why I make this format which will definitely help me as well as all other researchers in this field. Expecting resourceful and cordial cooperation.
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Dear Mashud,
I have some experiences in improving optimization algorithms like quantum invasive weed optimization algorithm ( ) and world cup optimization algorithm ( ).
From my experiences two point are important to select a good optimization algorithm:
1) check that do your problems can be solved by the classic methods? if so, do not go to the meta-heuristics.
2) If your problem was NP-hard and can not solve by the classic methods:
after a lot of testifying, I found that there is no more differences among the evolutionary algorithms. of course in some case, one algorithm may have better performance or has high speed, but this prominence is not so bold.
3) Two cases that you should point to them (in evolutionary algorithms) are: Exploration and Exploitation.
Exploration parameter is for places that you have no information about the search space anymore and Exploitation is about that you have an approximate solution for your problem and this parameter in this case finds better solution.
These two parameters comprise the structure of all of the optimization algorithms. for example, in Genetic algorithm, Mutation is an exploration parameter and crossover is an exploitation parameter.
So based on your requirements, select an algorithm that has promonancy about your considered parameter.
good luck,
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Is there any relation between block chain and inventory management?
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Dear Abu Hashan,
There are several examples here firms have used block chain in supply chain.
>>>>Diamond-giant De Beers uses blockchain technology to track stones from the point they are minded right up to the point when they are sold to consumers. This ensures the company avoids ‘conflict’ or ‘blood diamonds’ and assures the consumers that they are buying the genuine article.
>>>>>>There are several supply chain startups such as Cloud Logistics who saw an opportunity to provide blockchain-enabled supply chain solutions to improve efficiencies and reduce costs for the massive supply chain industry.
Hope that helps
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Sometimes its very necessary to find appropriate journals to submit articles but its also necessary to know the impact factor.
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@Abu Hashan Md Mashud
As a search engine, you can search https://www.scimagojr.com/ that contains the reputation journals but it has different calculations for the SJR factor rather the Thomson Reuters. If you need to check if it's a journal in the master journal list or not you can check the clarivity analysis master journal list (http://mjl.clarivate.com/ ).However, the Journal Citation Report (JCR) managed by Thompson Reuters, releases impact factor each year that can be purchased or some researchers may provide it for free (just needs some deep Googling).
Also, You can search the scopus website for the journal name https://www.scopus.com/home.uri
More over,, you can download the impact factors for journals in 2017 (Thomsen Reuters - uploaded by Murtaza Sayed ) here:
Some other links that may be useful (I'm not completely sure of them, but you can try)
Other documents uploaded by some reseachers:
Journal/Conference titles indexed in Scopus: List of Journal/Conference titles listed in Scopus, updated in 2018
InCite Journal Citation Report (Thomson Reuters Impact Factor) - 2018 (https://sites.google.com/a/koyauniversity.org/dqa/incite-jcr-thomson-reuter
Journal titles indexed by/member of the Directory of Open Access Journal (DOAJ), updated for 2018: https://docs.google.com/spreadsheets/d/1TF4FSlyyNIX6MdVUbD9zoLht2q3XhzerDe9Kf0k4DRs/edit#gid=719492038
Take care that ...many journals gave created their own impact factors which are fake.
Good luck
Samaa Shohieb
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I am trying to reduce edge build up/down and center buildup defects during continuous hot-dip galvanising process. During analysis it showed us it is mostly during air knife adjustments. We're using 1982 air knife design. If anyone can assist I would be grateful. I have done all the settings and procedure to be done.
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You can use edge guiders to extend the surface of sheet, it will stop the creation of negative pressure at the edges of sheet. But more easy option is try to use edge drop cold rolled coils. Try to drop the edges of sheet 10 to 15 microns from the center.
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The carotid shunt is made up of a tube on the extremities of which the balloons are glued during the manufacturing process. Quality control (functionality test) are carried out in order to ensure that the product is conform. It has to be ensured that the balloons suffer no leaks.
What are the possible quality control test (non-destructive) that can be put in place after the assembly process to ensure conformity of the product ?
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I tend to agree with Dr. Garry. During manufacture every 10th product should be tested by a competent technician, inflating the balloons to the recommended volume and seeing that they hold the air for a few hours.
Prior to actual use in surgery, the surgeon should make sure that he/she repeats the testing. Only this time it will only be for a few minutes. And it always pays to have a back-up Pruitt-Inahara shunt in the room.
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Two nozzles of different output diameters (0.20 mm and 0.25 mm) are being used to take mass measurements for an analysis over a time period for the same input pressure.
It has been observed that the standard deviation in the measurements increases in with an increase in diameter of the nozzle.
Is this true? Does an increase in diameter causes greater fluctuations in the flow for the same input pressure?
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You can consider two parameters:
1) the mass flow rate, if it is taken constant an increase in the diameter causes a diminishing averaged velocity.
2) the Reynolds number, if the averaged velocity is taken constant the Re number increases. From 0.20 to 0.25 you are increasing the 25% and the Re number can be such that transition to turbulence can occur,
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Is there specific KPI(s)?
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Demand variability is a measure of how much variability there is in customer demand.  It is the difference between what one expects to happen and what actually happens.  Demand variability is driven by several factors including:
  • The complexity of demand in general
  • Variation of demand across global enterprises
  • A lack of visibility within and across supply chains
  • Variable forecasting approaches at both the plant and customer level
  • Variable lead times at both the plant and customer level
  • Increasing inclusion of more suppliers and subcontracts
  • Increasing inclusion of smaller suppliers
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Is the ability of masonry cement to last longer in the workability phase, mainly due to the addition of gypsum during production, in quantities lower than that added to the cement used for reinforced concrete?
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It is best to experiment with your own laboratory according to the type of cement used and the proportions you would like to test
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Ideally I'd like to hear this from people working on shop floors in production engineering.
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E.g. supervisory control of an entire production facility
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How to classify manual tasks based on fatigue rate by using sEMG in Manufacturing Workplaces?
There are various tasks in manufacturing workplaces (Static tasks, Dynamic tasks, repetitive tasks and occasional tasks).
Can someone suggest papers related to classification of tasks based on fatigue rate using sEMG (Surface Electromyography) in manufacturing workplaces.
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thank you ...
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Am currently looking for new research areas in the Engineering management field, at the moment am considering lean and green engineering, but would appreciate any  additions or new area of opening.
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I think that you can work in "The seven losses". Little time ago appears an eighth losses about the human resources losses. This concepts are very interesting for work.
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Hi, all.
Wondering about Enterprise Performance Perspectives (such as postulated by BSC), each Perspective reveals an expectation expressed by stakeholders and managers, and it also may regard such as an "aggregation" of Performance Indicators(PI).
1. Please, what is your point of view about different expectations about PI values, in several Perspectives, keeping in mind the same organization and collect moment?
2. This situation would not be a conflicting aspect, revealing a conflict in Perspectives's Definition previously ?
For instance, in this hypothetical scenario:
  • Perspective-A, with PI-1 expected LOW;
  • Perspective-B, with PI-1 too, but expected HIGH;
  • Perspective-C, with PI-1 too, but expected not present.
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Thank you, Prof. Fitsilis.
On this specific case , we have confirmed the possibility of a conflict about PI role and different expectation about it by stakeholders.
What can we do to solve PI's conflicted objectives, which are not solved by strategist through a decision method and consultive approaches? This scenario reveals a deadlock.
This is my investigation point.
For a while, I wonder about the possibility to define an individual meaning of these PIs in each perspective (so called, abstraction), then after, constructing (or translating) in a concrete representation in each Perspective.
Regards!
AC
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Something related with Production, Drilling and Reservoir Engineering.
Thanks
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Hi Rui,
These are the current hot topics
Hydraulic fracturing
Enhanced oil/gas recovery
Smart well engineering
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I know I can destil it but is there any danger with the 99% product if drops are formed during destillation and fall down?
Isn't it explosive by falling down or friction??
Thanks very much.
Thomas WIllms
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Can you explain that in detail?
DOE has many equivalents....
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Several ac manufacturing company use steam activation to produce ac from coconut shells. I am writing up my doctoral thesis and I have utilized AC from coconut shells activated with steam. I think that I should explain the reason why this activation is used. Do you have any suggestion for me? or explanation?
Thanks!
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Activation with steam is cheaper (as water is indeed much cheaper than pure CO2), and requires lower temperatures (typically 700 - 800°) than CO2 (typically 900°C). For general-purpose activated carbons, the development of the porosity is far enough with steam, and therefore doesn't require the need of the much more expensive CO2, which produces narrower pores in general.
Alain
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customized production
latest Technologies allowing make-to-order production
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Dear Paolo,
I can suggest you the works of Vladimir Modral from Technical University of Kosice - he has written some important papers in the field of Mass Customization Manufacturing.
Some other papers:
Anisic, Z., & Krsmanovic, C. (2008). Assembly initiated production as a prerequisite for mass customization and effective manufacturing. Strojniški vestnik, 54(9), 607-618.
Bednar, S. & Modrak, V. (2014). Mass Customization and its Impact on Assembly Process' complexity. International Journal for Quality Research, 8(3), 417–430.
Hu, S. J., Ko, J., Weyand, L., ElMaraghy, H. A., Lien, T. K., Koren, Y., Bley, H., Chryssolouris, G., Nasr, N. & Shpitalni, M. (2011). Assembly system design and operations for product variety. CIRP Annals-Manufacturing Technology, 60(2), 715-733.
Modrak, V., Marton, D., & Bednar, S. (2015). The Influence of Mass Customization Strategy on Configuration Complexity of Assembly Systems. Procedia CIRP, 33, 539-544.
Mourtzis, D., Doukas, M., & Psarommatis, F. (2013). Design and operation of manufacturing networks for mass customisation. CIRP Annals-Manufacturing Technology, 62(1), 467-470.
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In India many companies follow Target costing. Some have exclusive departments to adopt Target costing in the new products as well as existing products. Me as research scholar would like to have some feedback from the fellow researchers on the number of major companies in different disciplines like, Machinery builders, Pharmaceuticals, Cement Industries, Food Industries, Textiles, Electronic Industries...etc. 
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As per earlier studies around 30% of the companies follow Target costing in their companies. Present status not known.
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I am doing my research work in TWECDM.
1) can anybody please tell me what is the new scope in TWECDM. And what are the new materials possible for machining. I have collect all the data which are required to set up machine. But Unfortunately I could not find the materials which is suitable for the machining. So, Kindly suggest me new materials for TWCDEM.
2) is it possible to do machining sodalime glass with TWECDM?
3) I have one doubt that what are the new MMC materials are suitable for TWCDM. 
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Thanks for giving answer..... But Lots of work is carried out in Zro2, And SiC..... I am trying to searching a new material.
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Lawyers, scientists, physicians, accountants and engineer are trained to think logically and observe ethics of their profession, but they use different method of problem solving. Their training and experience influence the way they think. Even for science based professions, scientists, engineers and physician solve their problem differently. Business leaders are advised to think like engineers, implying there is a value in it. How engineers acquire the mid-set they have? How can it be nurtured and transported to other professions.  It is said that engineers are success oriented, but “success” means different thing to different people.  Success for some is an idea becoming reality, for some an idea becoming a profitable business, and for some an idea to provide a pathway right to the bank.
There are also publication by the royal academy of engineers describing the traits of an engineer.  Few books on “think like an engineer’” were published recently. They use anecdotes to teach businessmen to think like engineers, but author themselves don’t think like engineers, since they use inductive logic rather than deductive logic. These authors begin with anecdotes, and then determine what general conclusions can logically be derived from those anecdotes. In other words, they decide what theory or theories could explain the anecdotes, then concluded that all should think like an engineers. This is a reasonable hypothesis given the data. However, induction does not prove that the theory is correct. There are often alternative theories that are also supported by the data. Such books may have an entertaining value, but no one becomes a thinker by reading them.
I am researching “how an engineer thinks?”  I appreciate if you would share your thoughts with me.
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Engineering is about creating a system that fulfills certain defined requirements. Therefore, the most important question an engineer must know is "what are the requirements?"  
Non-engineers tend to jump to thinking about solutions before they have clearly defined the requirements.  This causes them to forget or miss things the system needs to do.  
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I am doing research and need to predict flank wear in end milling. I need help to measure flank wear by using image process (ccd camera) and a microscope.
Can I use your method, and what is the minimum number of tools I need? Are there any other ways you suggest?
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In my last work, I employed L9 design for 4 factors & 3 levels & 3 responses with doing final confirmation optimum test, via Taguchi method. I explain about it, step by step in my article. You can see my article in below link.
Good Luck
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i am going to desig a rectangular type mug there will be three layers of inner will be of saag(teak) wood then middle will be of glass wool and outer will be of pvc. now i knew their thermal conductivities and the temareture difference would be 30-35 degree celsius.now i want to kwow how can i fix their thickness?
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you can find many data related heat transfer through composite wall..  so from that you can calculate thickness..
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Well testing reports for the appraisal wells and initial gas in place are the available information.What is the best approach to determine well gas flow rate and the number of wells required?
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This is a full topic by itself, Field Development Planning. 
There are multiple parts of the process: Geology, Petrophysics, Reservoir Engineering, Production Technology, Drilling, Economics, Environmental, Facilities .. etc (The list goes on).
To answer your question regarding the number of wells. I would say you can have 3 approaches. First, it is a gas field, so from P/Z plot and using GIIP for P=0, you can simply define the decline in pressure vs. cumulative production. Now, you know the minimum pressure (BHP/THP and thus reservoir pressure that no production at due to backpressure and thus you find your total estimated recovery). With this approach you need to be careful in case you will have aquifer or over pressure which might result in misleading material balance calculation. Once you got the total recovery, you already have an estimated rate per well per day from your appraisal wells. Then,
total volume recoverable/rate of well *365 (or 360 days based on your assumption*number of years you have the license for/planning to develop the reservoir for) = number of wells required for your field. You should however take into consideration that the lower the draw-down the lower the rate and thus your wells now producing high due to the fact the reservoir is still at initial pressure and by the time it declines, the rate decline as well. Simple Darcy law over different drawdowns and using the P/Z vs. Gp should give you good estimate. You need to take some margin during your estimate of each well rate due to turbulence, well damage, downtime .. etc
Second approach is bench-marking, you should really get pretty good estimate since the field is gas field and thus all you need is to know the total reserves to bench-market it against other fields that were able to produce such amount in certain period of time.
Third approach (which is the the long one) is to start building static model and dynamic model and start increasing the number of wells (try to put one well per drainage area you obtained from your welltest to prevent interference) till you finally have the total number of wells.
If you need a good guide for writing FDP, please send me a message and I will send you something pretty useful.
Good luck; (you might have finished this work already, but I am answering it for people who see the question and/or as a future guide for you).
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Information sharing and exchange between OEMs and suppliers is a new approach to enable responsiveness.
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Besides smooth flow of information, the process includes smooth flow of materials from suppliers, smooth production and smooth delivery to end customers.
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As a beginner, I have some queries regarding Dodge-Romig AOQL Table as follows:
1. If the rejected lots are 100% inspected (normally), then what is the objective of selecting a sample size using Dodge-Romig AOQL table (because we already know about the lot)? I find that if I inspect each and every item of a (rejected) lot, then selecting a sample size using AOQL table makes no sense.
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Dear Parag,
The main idea is to minimize the cost of inspection and any delay associated with inspection for GOOD lots. Therefore, the plans were designed to accept the good quality lots with minimum inspection. 100% inspection was reserved only for BAD lots, those that had more defectives in the sample than specified.
Good luck.
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Conceptually can two existing semibatch distillation assets substitute for a 3 outlet continuous divided wall column, accepting lower thermal efficiency.  Think semi commercial scale.
Specifically, are there heuristics to follow for this comparison, given all column dimensions, and stages, so that the alternative flowsheet, has a greater success at being capable?
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You are welcome
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I am conducting a research project about sand production control in oil wells. And I am in need of good references to rely on while conducting my research. Any help would be appreciated.
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My goal is to propose a methodology to assess the economic and environmental impact of a new equipment/technology/production system in manufacturing or remanufacturing processes by using simulation and proper KPIs
I wonder:
  • what are the potentials and the shortcomings in using simulation (discrete event simulation particularly) for this kind of research goal
  • what are the alternative research methodologies (beyond that one above) to address this research goal.
I warmly embrace answers ranging from the sharing of experiences in this field to references, when clearly connected to the topic.
Thank you.
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Dear Ilaria,
It is very critical to determine some key performance indicators (KPIs) to track the changes. In this regard, you can do a literature review and find which factors are more critical for what you mentioned in your question (e.g. total production cost and cycle time for economic or CO2 footprint for environmental perspective). Following are some required steps:
1. Construct the current model and run it using the real data. Use KPIs as the model output (e.g. cycle time). Run the model for many times and check the report of KPIs.
2. Construct the new model, run it and check the same KPIs.
3. Compare the outputs. Is there any significant improvement?
4. Do a cost/benefit analysis. Can the achieved benefits justify the assigned costs?
5. Do a qualitative analysis (e.g. social perspectives) on the achieved benefits.
(Suggested software: Arena or ED)
You can check the following paper :
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In EDM process, tool wear is almost inevitable and wear characteristics do depend on tool electrode material properties, flushing conditions etc.
But will tool wear be affected by the work piece properties? For example a material like titanium which have poor thermal conductivity is difficult to machine and the machining time will be very high in comparison with the same for a material like stainless steel. 
My doubt is, apart from this longer machining time (which will result into prolonged exposure of the tool electrode to discharge conditions and may result in relatively higher wear) does any property of the work piece material (say thermal conductivity) will have a direct influence on tool wear?
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Of course, removal rate and wear of the electrical and thermal properties of the electrode materials are dependent.
The metals and many alloys can be assumed that a good electrical conductivity is also in a good thermal conductivity. The tool electrode should have very good thermal conductivity, because then through the lower energy density in the spark-base point, the energy is more easily dissipated, and there is less melting and evaporation of the material. When the workpiece matter is a bit more complicated, because I do not have the choice there, but wants a material ED edit. The different concentration of the energy density in the cathodic base point can oppose an appropriate shaping of the machining pulse. It makes a difference if I flat, smooth surfaces wants to finishing, or in the roughing a deeper insight erosion.
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Can be determined from the various models, a transition region? Is it possible that in one area, both processes can take place?
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It is a damn tough question, yet it is important to correctly decide has to look like the process energy source and process control. If one begins with the μPECMM (double-layer-reloading), then mostly worked with sufficiently short pulses and small current amplitudes. Critical is the situation when in the "conventional" ECMM the pulse durations are steadily reduced. The relatively large work surfaces, then also require larger currents, so that it can not be easily made it.
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I am specially interested in languages capable to deal with dynamic and stochastic environments.
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Why don't you use GANTT chart for this purpose? It can represent the practical scenario of production, like raw material arrival, set up, dynamic change in production capacity, disruptions, bottleneck, and so on.
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This would help me include the papers or journals as references and also study their work to find out their limitations and carry out further studies on their work.
Thank you.
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The following information may  be useful for your research
A welding procedure (WPS) for MIL A46100 steel armor joints using the gas metal arc welding process (GMAW)was developed and qualified according to mechanical and non-destructive (NDT) requirements of military codes. Obtained results
were compared to shielded metal arc welding (SMAW) procedures used to weld this type of steel. It was found that designed WPS is a suitable option to weld MIL A46100 armors according to the results obtained. In addition, a narrower heat affected
zone (HAZ) was obtained with designed WPS which should lead to a better in-service armor performance according to results of previous studies. Finally, an increase in Charpy v-notch (CVN) test impact energy compared to the SMAW procedure was found
DEVELOPMENT OF A WELDING PROCEDURE FOR MIL A 46100
ARMOR STEEL JOINTS USING GAS METAL ARC WELDING
DAVID MAZUERA ROBLEDO, JOHN ALBERTO SUÁREZ GÓMEZ J ORGE ENRIQUE GIRALDO BARRADA
Dyna, año 78, Nro. 168, pp. 65-71. Medellín, Agosto, 2011. ISSN 0012-7353
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Operational risk is a concept from the area of ​​financial risk. The definition is contained in the Basel II regulations. On the other hand, there is the theory of machines safety, occupational safety, environmental risk through production. It seems that the same issues come up quite differently from economists and production engineers. Maybe there are some models that integrate these issues?
The problem lies in the risk (human, economic and environmental) assessment of the designed method of production, in compliance with the terms occurring in the theory of operational risk (Basel regulations).
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From my perspective (even as a former regulator) Operational Risk is to  be measured on a much broader basis than the financial sector: Unfortunately, I am not Aware of any mathematical models for the theory of machines safety, occupational safety, environmental risk through production but I would expect that one easily adopt these approaches for certain Operational Risk Problems in financial institutions as well: Hence, from a mathematical point of view I would expect to see different applications for the same mathematical techniques (as, e.g., any loss distribution approaches, Markov chains, etc.).
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We know that the problem with release dates is NP-hard.
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I don't think I understand your question.  It is never optimal for the machine to be idle if all release times are 0.  Proof: if the machine is idle for epsilon time units, change the schedule by doing everything after the idle time epsilon earlier.  The weighted completion time will decrease by n times epsilon where n = # of jobs completed after the idle time.   A similar argument called "swapping" proves that preemption is never optimal.  Suppose job a finishes before job b finishes, but job b runs for a while before job a finishes.  Make a and b trade epsilon>0 time, where b gives a time before a finishes and a gives b time after b has run for a while.  Then b's finish time stays the same but a's finish time is strictly better.  Swapping is also how you prove that if job a has larger weight/runtime than b, then a should be scheduled before b.  If not there will exist two consecutive jobs that violate this ordering rule.  Swap them.  It's a simple computation to see that the sum of weighted completion times strictly decreases.
If this does not answer your question, please clarify what you mean about idle times.
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bcoz NaCl is cheaper than si substrate
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1-The substrate have some property. Compare to NaCl and Silicon the substrate property is good in Silicon. NaCl is weak substrate.
2-The Modulus property (young's,shear,rupture) all are having many times better in Silicon.
3-The NaCl having 100 as a cleavage plane but silicon cleavage plane is none.
4- Silicon have the high temperature withstand property than NaCl.
Till now NaCl is not having the capacity to fight with Silicon.
So, comparatively Si is better than NaCl. Till now NaCl is a research grade substrate. Silicon is one of the best substrate, so it is mostly used in industries.
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Many researchers argue that EDI (i.e. Electronic Data Interchange) technology does not provide flexibility, arguing that EDI is out of date technology. To what extent is this claim valid? To which industry sector to this valid? What is the alternative?
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Intranet technology is already adopted by most of the system suppliers. The new trend is to use Enterprise Content Management Systems for sharing not only of documents but sharing of real-time dynamic production data. A good approach is to extend the existing functionality of existing CMS (like SharePoint) with additional Manufacturing Operations Management (MOM) functionality, such as ISA 95 objects, OPC, BAPI, etc.  
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I want to explore how to make strategic management to manage solid wastes in an industrial area in a developing country. What is the proper method for this? SWOT analysis and/or any other recent methods?
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Dear Emma, 
In order to be useful for drawing up the strategic plan, as Deshmukh says, I suggest to use Life Cycle Assessment (LCA). There are several studies that deal whit solid wastes and LCA.
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I want to calculate the optimum height of bench in phosphate mines.
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Bench height in mines is a function of many geotechnical , production and economical parameters. Mostly these parameters are empirical and based on different conditions.
Some good books with chapters containing a lot of info on bench height calculations:
1-Handbook of Mining and Metallurgical Engineering
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At 5000 ft and no water drive.
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It's too deep for SAGD, where you can have up to 70 % of OIIP Recovery. Try Cyclic Steam-Hot Water flood. Expected Oil Recovery is 20 % in Silicates, 5 % in Carbonates.
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I'm working with multi-criteria analysis applied to manufacture processes. However, I'd like to include in my study only the most relevant manufacturing metrics available. For example, some common metrics are:
- Manufacture defects
- Degree of availability
- Production capacity
- Cost
- Cycle time
- Etc
I believe that they can be summarized into 3 main metrics:
- Cycle time
- Process efficiency
- Cost
What do you think about it? Any feedack is welcome! Thank you
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Your question can probably not be answered in general as manufacturing systems are too different. When you look at the manufacturing of cardiac catheters it is obvious that cost is secondary when you don´t manage to get quality right. So stability of process and absence of faulty products are the dominant factors. In automotive industry you very often find the combination of forming presses (extremely short cycle time, very long set-up times) and following welding procedures (long cycle time, no or little set-up times). So in these cases lot sizing and stock (cost) as well as set-up times are relevant criteria. Faulty products are easy to detect and can be discarded without mayor consequences. And there are many more examples.
For your cases it seems to make sense to define a manufacturing process or a category of processes you refer to.
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Please mention some AMTs that are useful for the textile industry.
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Thanks Mr Ezazi,your experience was so helpful for me.
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Especially at the board level
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Production engineering deals to all managements production problems such as manufacturing system design problem