Best Seller Books-Operation Analysis |
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Production and Operations Analysis
Once I have reviewed this book is a nice book for introduction to manufacturing system for undergraduate level for industrial engineer. The book covers Forecasting, Aggregate Planning, Inventory control (certain and stochastic demand), Push vs. Pll Production Control Systems, Scheduling, Facility Layout, Facility Location, Quality control and Reliability. Which already covered in the munufacturing required.
However, In Forecasting chapter, the book provides a lot of good basic forecasting methods such as moving average, exponential smooting, trend-based method, and seasonal series. In Aggregate Planning chapter, the book covers just the basic concepts and models which can be done better. For inventory control chapters, the book does a nice job and cover a lot of detailed basic models which is a good introduction. In the Production Control Systems chapter, this book also has done a nice job in covering detailed basic ideas of the MRP subject such as lot sizing methods in MRP but JIT section could be done better by adding some more detaile on key factors of JIT’s success and the use of time buffer instead of inventory buffer. In Scheduling chapters, the book covers a very basic models for scheduling which is again good for introduction.Finally, The rest sections of the book are nicely written with the level of introduction. Overall, this book is good and nice to have. One comment on the cover page is that the formulation for EOQ is very wrong and should not happen for the book on manufacturing system.
Author :Steven Nahmias
Professor of OMIS
Director of Faculty Development and Research
Dr. Steven Nahmias is a Professor for the Operations & Management Information Systems Department in the Leavey School of Business at Santa Clara University. He holds degrees from Queens College, Columbia University, and has a Ph.d. in operations research from Northwestern University. He is the author or co-author of more than 50 technical papers, which have appeared in a variety of journals and books. He has gained an international reputation as an expert in stochastic modeling. Dr. Nahmias has served as an associate editor for Management Science and Naval Research Logistics, and the Area Editor for Operations Research, and was a founding senior editor for the Manufacturing & Service Operations Management. He currently serves as an acquisitions editor for Business Expert Press.
Dr. Nahmias is the author of Production and Operations Analysis, published by McGraw Hill. The book, originally published in 1989, is currently in sixth edition (2009). More than 100 colleges and universities world-wide including Stanford, Berkeley, MIT, and the Harvard School of Business have adopted the text. It is used in both schools of business and schools of engineering, and has been translated into Spanish (two editions), Hebrew, and Chinese. Dr. Nahmias has been at SCU since 1979, and during that time has served as Department Chair (1987-1991) and Director of the Competitive Manufacturing Institute (1991-1997). He as also served on the faculties of Stanford University, Georgia Institute of Technology, and University of Pittsburgh. Dr. Nahmias received the University award for Sustained Excellence in Scholarship in 1998. In June 2010 he was honored by being named a Distinguished Fellow of the Manufacturing and Service Operations Management section of INFORMS. There are only 25 Fellows world-wide. Dr. Nahmias has also had considerable consulting experience. He has served as a statistical expert in several legal proceedings, worked with the Shaklee Corporation, Lex Automotive, and Tropicana on inventory management problems, and been active in many other projects.
The Operation Analysis And Optimization Model for Heavy Equipment Selection
When comparing results related to the rock material, it is clear that the developed model has limitations when applied to earthwork operations involving rock material. However,
economical optimization of equipment fleet operating on diverse types of soils proved the workability of the model.
Moreover, multiple assumptions made in this case study had significant impacts on model results. For example, tire penetration was assumed to be 3 inches. If this value was to
change, the optimum fleet would be instantly affected. Also, the productivity was estimated based on an off-site methodology. For more accurate results, the data should
always be obtained from the actual site and historical data.
The overall results showed that the accuracy of the model varies depending on the soil type, tire penetration, altitude, travel time, and project duration. Also, model results may be improved by implementing a comprehensive owning and operating costs module. The results of this study are anticipated to be of major significance to owners, general
contractors, and construction managers. Also, the proposed model would contribute to the database of fleet management systems by including a computer-coded model that integrates heavy equipment operational analysis with its correspondingeconomical analysis.
REFERENCES
Four layers of media analysis of patents on R & D Strategic
Overview – The need for information
In today's global, innovation, a highly successful and market leading technology will have the following characteristics:
1. A strong base of R & D investment;
2. A large number of qualified scientists and engineers;
3. A skilled and flexible workforce;
4. reliable utilities and other infrastructure;
5. competitive investor and tax environment, and last but not least.
6. Information about the patent landscape. L 'Importance of information on the patent landscape is of great relevance in this document.
Business Challenges
100% of a unique patent information for effective decision-making
competitive and integrated portfolio of patents with broad strategic objectives
Organization wide collaborative platform for brainstorming ideas
Monitor and track the competition in the cost of potential patent infringement
The solution of the community of R & D to look atCompanies face the challenges of business shown "beyond the information technology and intellectual property."
Four levels – the Nexus with intellectual property (patents) and Information Technology
The four tiered approach for the detection of patent information is submitted to be unique to the development of "Beyond Information Technology Intellectual Property and Beyond" strategy.
The framework proposed 4-layer is expected that a valuehas the solution to one of the best approaches Mark. This will also provide much-needed focus on the search strategy.
Beyond Information Technology
The fundamental problem addressed by the technology of information products, ie, the patent is not Gender analysis tools used to justify the software, the aim is a complete analysis of patents. An interactive Web page, the dissemination of patent information more readily reproducible and is accessibletraditional forms of scientific communication and education is the need of the hour. Patent information on the interactive website experienced a general rule, a cross-functional team working in tandem. develop the following sections of this article would have a deep understanding of the four-layered to capture information on patent applications. The approach mentioned here include highlight the aspect of the exchange of information requested by the researcher during patentDetermining the focus of research.
Beyond the intellectual property
During the previous years, file sharing networks on data from the database so-called patent or patent in what is now the largest, most diverse archive of patents and more readily available in history has grown. Although the availability of Internet bandwidth at low cost and storage space or the North is separated from the South, is one of the most far-reaching sharing of files that access is nowInformation on the web. Of particular interest is the question of the archive: At a time when the file-sharing networks form the largest collection of patent data that has ever existed, the focus shifts from the interests of individual users' files of patents in particular groups and institutions and their desire to organize, make available, secure and make the data of the patents. The current approach requires dealing with companies with a research focus with less contentProvider "(the dump information to the consumer), but increasingly with" context provider "(ie information instill in the social networks of production).
A layer – Data mining
to understand the countless number of patent information from patent databases around the world and a challenge for the extraction. The concept of a patent search in these databases is developed in an explicit gender in science. Patent research is a tool to obtainThe data relating to a particular field of knowledge. Other information may be reservoirs of white papers, presentations, national and international periodicals room and finally the pages are allocated. Patent Search science for the purpose of the patent landscape design process begins first with the preparation of a study on the basic concept of a lookup table. This study is to find detailed information about patents and non-patent literature cited is available from sourcesbefore. A table concept of research is used as a platform to organize and rationalize the role of applied research relevant patent databases for each other. This search method patent serves as an index for the various concepts together are trying to analyze the keywords used in the form of a search term. In addition, data extraction level for the preparation of strategy research. For example, the table search strategy, with an area of the users concerned andThis table is essentially the number of visits per stroke research, production run / publication for each search query, etc. The attempt of this topic, or data mining is conducted with great care must be executed. Otherwise, the whole target, search for the patent landscape and then gain the attention on R & D is vulnerable to derail, as did the other three layers heavily on this first layer to their effectiveness.
Layer Two - Data AnalysisData Cleansing &
The assumptions of this layer is derived from the result of the layer of data mining. Despite the skills of the team to perform the extraction of data and processes are carried out without interruption, the results are intended to be prone to contain false documents. Therefore, it is one of the main objectives of this layer to clean the data and make it free of false documents. The normalization methods used here generally recordConsolidation of company names that the names categorization patent applicants' technology, etc. In order to ensure the normalization error-free, patent databases to retrieve form source to the corporate structure. Many times it is the patent landscape team the authority to determine the technology classification of patents. It 'so important that a functional team, a multitude of experts to provide a solution to a crisis.
Three layers – dataIntegration, patent valuation
Data integration is simply the collection of multi-source, multi-platform information in a recognizable format. This layer is also fully responsible for the elucidation of the taxonomy in a mental map, which is considered useful by companies for the organization of patents, etc. The specific instruments to try to draw the mind map on hand. For example. Mindpro Manager. Also designed an interactive map of the mind, which is in response to mouse clicks in the data veryIntegration. Data integration is also available from the extrapolation of missing information on the results from previous levels. Eg., Is not that the information on patent assignee patent pending. It is therefore imperative that the team is based on non-patent literature for this purpose. But in real situations is the use of non-patent literature is not a requirement, so that a primary in the depth of research must be done in a comprehensive manner.
Evaluation of patents from primary research
To understand the primary research capability that allows the collection of data from patent holders that in turn helps if the patent is a prototype with proven results in the laboratory stage for non-life science patents. For life sciences, the understanding of in vivo models for testing and the results were used for-. Further understanding to interpret toxicological data in life sciences and to ensure the multiple use of a particular patent is advantageous. L 'primary research data collected at this stage is simply incomparable to any of the secondary research data in the wide range of data sources. Therefore, the approach to primary research and should be taken with reasonable assumptions on the base.
Step Four – Presentation of data
level of reporting is formulated with the help of the wiki. Wiki is an excellent tool for collaboration and exchange of information will be used within distributed teams.In addition to the wiki, a careful examination has revealed the club with the requirements of the need for a dashboard. The Dashboard is a Web 2.0 solution that works inside the web browser. Categorization of patents displayed on the dashboard, on the basis of taxonomy in the first layers arrived. The dashboard is also information on the distribution of patent applications company, and Time Line, you can click patent to read the title / abstract / information request. The patent documents in PDF format canbe reviewed and filtered for later use. Dashboard is a simple, but powerful tool for collaboration and is used by dozens of the largest companies in the world for common use and management of large numbers of patents, products and literature.
There are benefits / expected
The four tiered approach mentioned in this document has been used in many organizations Tier I belonging to a wide range of industries. However, the following services through inevitableOf course for any organization (large or small), which refers to best practice.
1. Save hundreds of hours for a research project to add thousands of hours saved – worth several hundred thousand dollars
2. Guide to new product strategies, which can result in many billions of dollars of new product opportunities
3. Lower process costs (in millions of dollars per lawsuit) against potential patent infringement cases
Space analysis
In addition todeveloped, identifying the space proves to pursue the necessary competitive edge so as to allow an analysis of patents. space analysis provides a breakdown of the classification of patents into smaller segments with only 7-15 patents. This allows research on a particular area, full bar for the future development of the product is considered to be focused. The analysis of white space helps local patenting potential of busy areas.Marking a cross against a specific ingredient that show their use. Finally, the white areas in the table shows the possibilities of a company car and patents.
Conclusion
Although conventional E 'was to facilitate the emerging needs of the efforts of R & D within a company to stay the concept of using the multi-level supports the UN researchers touched. Company is looking for such a service for leading global knowledge society tend Serviceto get a better return on investment for funds from the budget of R & D Enterprise.
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The five key elements and the five key steps to success Branch Planning Division
Operation / sector plans, objectives, planning and resources, the institution to achieve the growth objectives of the business unit, department, o.
Analysis of the options is useless if it does not work degenerate. operational planning, work, by definition, action plans for day after day.
Field Operation Planning
The five key elements:
1. A definition of services
2. The initiatives that support 'End Game Vision Branch — What are the objectives?
3. A review of the available synergy
4. A commitment to the timing and sequence of major steps
5. An agreement on the metrics and goals
The five main steps
Step 1 – Definition of services
Criteria:
or must be forward looking
or must focus on the external environment
or must consider the local competition, customers and products
or to examine the branch of weaknessas well as strengths
strengths or needs of the local market must comply
Typical applications:
o What is the purpose of your company?
business or what you are now?
o What companies should be you?
o What are you all right?
or what you have failed?
o What differential advantage you have over your competitors?
o What differential advantage that they have on you?
o What markets do you serve?
Step # 2 – The IndustryGoals?
individual support for industry initiatives that the end of the game must be identified. These initiatives include not only the financial goals of families, but they also need the support of all non-financial goals in the final, so far deferred identified.
Step # 3 – A review of the available Synergy
Synergy occurs when two actions together produce a greater profit than they would if run independently. If 2 + 2 = 5
InfluenceFactors
O optimal scale of operations
or Extension Methods
O Negative impact – 2 + 2 = 3
O Knowledge / knowledge transfer
Step 4 – Commitment to the timetable of the main steps
Since resources are always limited, a store manager has to decide what to do first and what to move. A process of action planning must for any initiative that supports the end of the game occur. specific responsibility, the expected results for each phase of the plan and the completionDeadline for each phase of the plan is essential.
Criteria:
1. The reaction is serial in nature
2. parallel can be used
3. Determine the opportunities of non-
Step 5 – An agreement on the metrics and goals
Typical criteria:
1. Return on Investment
2. Danger of losing investments
3. The company's growth
4. Contribution to social welfare
5. Stability and job security
6. PrestigeCompany
7. Future controls
8. Inventory turns
9. Fill rate
10. DSO (Days Sales Outstanding)
11. Cash to cash cycle
Remember:
job or job description + + + = tangible result Head Date
o The action item is a bit of "bite-sized" work to be completed before an event review.
or an effective introduction requires great attention to the resources available, for example, time.
O = Responsibility + Accountability Authority
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Characteristics to watch out for in monitoring software for backup
To ensure that backup operations running smoothly, companies need to look for certain features of the monitoring software backup. These features are a variety of term and long-term benefits to short, including the efficiency of daily operations and reduced capital spending on System Tools. The following features:
1. Using Web 2.0 technology – Web 2.0 focuses on dynamic content and acceptable that a giant leap from static Web pages or content. For data managementIn particular, the software must be able to provide easy access to reports and an individual way to organize the necessary information.
2. Accurate Reporting – software for monitoring of backup should be able to work to present accurate and highly detailed data about the status of the backup. Important information to know the backup administrator, the success / failure rate is the cause of failures and synthesis of backup and recovery. In this way, the administratorable to tackle obstacles to the operation.
3. Predictive Analysis – The software must not only figure in the current language, but the base must also be capable of a forward looking analysis of the figures. This feature will allow companies to standardize the precise use of their storage media and know more or less when the plates will reach its maximum capacity. Additionally, the prognosis leads to an optimal use of tapes or discs,Create savings for the company.
4. Ease of use – the management of backup should not be a difficult task, especially for people whose technical skills are in high school. To increase the ease of use, the software must have controls that are easy to understand and a display panel that can be customized to present only what is important to you.
backup monitoring software with these features to simplify and streamline data management activities. Entrepreneursyou should check when customers to backup solutions.
