Sunday, October 2, 2016

New Technology Adoption - Management Guidelines

Godoe, P. & Johansen, T.S., (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European Psychology Students. 3(1), pp.38–52.

Organisations adopt new technologies to improve the efficiency and effectiveness of various work processes. Unfortunately, many technology-based products and services never reach their full potential, and some are simply rejected (Burton-Jones & Hubona, 2006). Failed investments in technology may not only cause financial losses, but also lead to dissatisfaction among employees (Venkatesh, 2000).

The technology acceptance model (TAM) has come to be one of the most widely used models. The two primary predictors in TAM that affect technology usage are perceived usefulness and perceived ease of use.

The other paradigm focuses on latent personality dimensions to explain the use and acceptance of new technologies (Porter & Donthu, 2006). In other words, an individual's personality influences the potential acceptance of technology in general. The technology readiness index (TRI) (Parasuraman, 2000) follows this approach. Technology readiness can be viewed as a gestalt resulting from four personality dimensions: optimism, innovativeness, discomfort, and insecurity. According to Parasuraman (2000) these personality dimensions affect people's tendency to embrace and use new technologies. In this respect, optimism and innovativeness function as mental enablers, while discomfort and insecurity function as mental inhibitors to accepting new technologies.
In the last decade, research has emerged combining the two paradigms by integrating the TRI and TAM into one model. Lin, Shih, Sher, and Wang (2005) and Lin, Shih, and Sher (2007) included technology readiness as an antecedent of perceived usefulness and perceived ease of use in TAM. Walczuch, Lemmink, and Streukens (2007) took a somewhat different approach by investigating how each dimension of technological readiness affects the predictors in TAM.

Beating Murphy's Law in New Technology Adoption

MIT Sloan Management Review, Spring 1991
W. Bruce Chew, Dorothy Leonard-Barton and Roger E. Bohn

Beating Murphy’s Law - Steps

Rule #1. Think of Implementation as R&D

 Acquisition of new technolgy  should  be considered an ongoing process of data gathering and learning that evolves over time. Initially, an organization must focus on technical data regarding equipment options and costs and a study of existing applications. Eventually, the technology goes through startup and data is generated in-house. But in every phase the goal is to learn all that can possibly be learned at that point in time. In effect, the introduction of technology should be considered less as an investment issue or technical issue and more as a question of research design.

The experiments should address both technical and organizational questions. Managers who understand that they are managing organizational change, not just technical change, are better positioned to direct the learning process. The work of technology managers should include: working very closely with users, whose role should be as codevelopers rather than receivers of the technology; constantly redefining the necessary support structure in the user organization, identifying and targeting potentially weak links; enlarging the definition of the technology to include the delivery system or other linkages on which the technology is critically dependent; and experimenting as consciously and productively with organizational forms as with technical ones, capitalizing wherever possible on experiments occurring naturally in the company.

Rule #2. Ask “What made it hard?” Not “How well did it work?”

The firm must look for answers to questions  of technology implementation like “How did you make this technology work? What had to be changed? What was hardest?”

Our studies suggest that technical knowledge, about the hardware itself, transfers more easily than organizational knowledge,

Rule #3. Learn in Many Ways at Once

Broadly speaking, there are four methods of learning that a firm can use:

vicarious learning—learning from the experience of others;
simulation—constructing artificial models of the new technology and experimenting with it;
prototyping—actually building and operating the new technology on a small scale in a controlled environment; and
on-line learning—examining the actual, full-scale technology implementation while it is operating as part of the normal production process. A clear hierarchy exists among these four methods: costs get higher moving down the list, but so does fidelity.

Managers in our studies consistently underinvest in preimplementation learning, choosing in effect to do most of their learning later, when it is most expensive.

Many managers appear unwilling to invest in learning by methods that offer less than perfect fidelity. They fail to recognize that learning need not be all or nothing. Another plant’s experience will not be completely relevant, but it is still possible to identify some issues that can be addressed vicariously. Similarly, simulation and prototyping can be effectively targeted at specific questions.

The consequence of these two competing hierarchies is important: use a mixed strategy for learning. Learn as much as possible using the low-cost, low-fidelity methods, but realize that some learning will probably be necessary from all four methods.

Furthermore, the ideal learning strategy includes parallel and simultaneous use of all methods, not just sequential use. For example, opportunities for improvements that are not uncovered until die prototype is running may become the target of simulation. Prototype pilot lines should be kept going in parallel with the main production line, as test beds for diagnostic experiments and trials of changes. Both technical and organizational learning must be documented and remembered. As noted earlier, one plant’s Murphy’s Law disaster is another plant’s opportunity for vicarious learning.

Rule #4. Simulate and Prototype Everything

 A simulation of a new technology is a model of how it will work. Simulations can range from simple mathematical models such as spreadsheets, through elaborate Monte Carlo computer models, to physical models of the entire plant, before and after the new technology is introduced. For example, in the steel industry it is common to simulate changes using scaled-down models with water in place of molten steel.

Simulation technology has improved dramatically in recent years due to advances in computer hardware (engineering workstations and personal computers are more than adequate for simulations of most production processes) and especially in easy-to-use, special purpose simulation languages. It is often possible to do a crude but useful initial simulation in less than a week of effort. In fact, we recommend that any new technology involving more than a few person months of total effort should probably be simulated in some way. Complex or large technology should usually receive several simulations targeted at different levels of detail and different aspects of the total system.

A prototype is a small-scale construction or isolated version of the final system for learning purposes, using methods as close as possible to the final technological target. The purpose of prototyping is to learn about problems and opportunities that were not found during the simulation but that will cause delays or expense if they are left for on-line learning.

Rule #5. “Everything” Includes the Organization

Simulation is equally applicable to organizational changes, though it is rarely applied. To implement a new MRPII system, the implementation manager persuaded representatives from all the potentially affected functions (shipping, purchasing, inventory, etc.) to come together in one room for several days to go through a noncomputerized simulation of the information flows The simulation served to educate the various functions about the coming system. The supervisors got to know each other and talked about the process interdependencies that the new system was going to cause or exacerbate. Because they came to understand the needs of other functions, whose representatives they often had not even known before, the participants negotiated compromises and agreements that forestalled problems when the actual system was implemented.

Organizational prototyping, like technical prototyping, is the execution of a design on a small scale for the express purpose of evaluating that design from an organizational viewpoint.  With organizational prototypes managers can anticipate needed alterations, potential pitfalls, and opportunities for additional benefits by observing the technology-organization interaction in microcosm before launching the full-scale production change.

Pilot runs of a new technology offer the opportunity for organizational prototyping, but they are rarely used for that purpose. Usually test runs are conducted by technical staff to learn about potential problems in the physical system. Litde attention is paid to the possibility of learning about organizational effects and opportunities, such as changes in roles, conflicts with existing rewards and incentives, differing responses to and use of the new technology depending upon operator background and skill, the different meaning that the technology has for different groups of users, and the most effective organizational structure.

Rule #6. Follow Lewis and Clark

The problem is not with planning per se but with the substance of a plan.
When Lewis and Clark headed west from St. Louis they did not attempt to specify in advance their exact trail and how they would cope with each expected contingency. They realized that the wilderness ahead was too unknown and the contingencies too many. Rather, they set out with a general sense of their route (up the Missouri River and over the Rockies), a good store of resources, and a team that had familiarized itself with everything known about the wilderness ahead.

Too often managers forget that new technologies have more in common with Lewis and Clark’s wilderness than today’s travel. thing go awry. Planning must provide a guiding structure for discovering and solving problems. It should focus more on what to look for and think about than on what to do. It should plan for an expedition of discovery, not a drive to a relative’s house; it should be a research design, not a recipe.

Rule #7. Produce Two Outputs: Salable Products and Knowledge

Eventually, the new technology is up and running. The new process produces not only salable products, but also usable knowledge. Production time, management time, labor, and materials should be budgeted for making both types of output.

Budgeting Time for the Seven Rules

The core of our argument has been that to beat Murphy’s Law it is necessary to plan for and manage directed learning. Anything you don’t learn about early will hurt you later.

One simple solution is to budget for this learning time throughout the project schedule. In particular, keep a reserve of production time for on-line learning in the first several months of startup. This is over and above the planned lower output during startup. Ten percent of production time is a realistic amount if vicarious learning, simulation, and prototyping have been done thoroughly.

The Rules in Practice: Different Kinds of Knowledge

In summary, managers typically underinvest in learning both before and after startup. This is particularly true of the organizational changes relating to new technologies.

The seven rules reflect a different vision of what it means to implement technology.

In all the most successful sites, investment was made in the creation of local user-experts, whose job it became to anticipate, model, prototype, and teach the new behavior necessitated by the technology, especially during the critical period of change from the old to the new system.

Tuesday, August 2, 2016

Manufacturing Management - Introduction

Manufacturing Management - Introduction


Narayana Rao

All Rights Reserved

Version 26

Last edited: 12 Sep 2011

Exported: 26 Nov 2011

Original URL:

Planning, organizing and controlling manufacture of goods is manufacturing management. Chase et al. define operations management as the design, operation, and improvement of the systems that create and deliver the firm's primary products and services. Operations management is a discipline that includes production of goods and services.

Once the company decides to manufacture and sell a product, the specialized responsibility of the manufacturing management starts. But the decision to manufacture a product is based on feasibility analysis. During this analysis also manufacturing management issues are involved. Therefore, the persons doing strategic analysis or corporate planning analysis include persons from manufacturing management discipline with manufacturing management knowledge and bring into the analysis or decision making process the manufacturing view point.

Manufacturing is carried out through processes. A process is any actvity or group of activities that takes one or more inputs, transforms them, and provides one or more outputs. The output could be for an external customer for sale or for an internal customer to use for further processing. In some cases it can be for consumption in the same process or by the consumption by the producer hmself. Manufacturing processes convert materials into goods that have a physical form.  The transformation processes change the materials on one or more of the following dimensions:

1. Physical properties
2. Shape
3. Fixed dimension
4. Surface finish
5 Joining parts and materials.

The outputs from manufacturing processes can stored and transported in anticipation of future demand (Krajewski et al. 2007).

Important Developments in Manufacturing Management

Developments in manufacturing management include certain technical developments that made manufacturing systems more productive and flexible.

Shopfloor management guidelines provided by F.W. Taylor were landmarks in the field of manufacturing management. Taylor further development Scientific management philisophy. Taylor also brought out the importantance of scientific studies in manufacturing processes improvement or design. His studies on machining were considered a very important research contribution. Taylor also introduced time study based best practice identification and training all operators in the best practice. He advocated that manufacturing managers have the responsibility of developing manufacturing methods and training operators in best methods.

Frank Gilbreth developed study of motions of operators to develop efficient operator movements either to do manual work or to operate machines. He and Lilian Gilbreth also introduced the concept of fatigue and proposed ways to prevent the negative consequences of fatigue in operators as well as in manufactuirng systems.

Henry Ford introduced moving assembly lines that revolutionized the production systems. Henry Gantt developed charts that helped scheduling production activities.

Harry Emerson wrote a book on principles of efficiency and it became part of industrial engineering and scientific management literature. Focus on efficiency in systems in general and especially manufacturing systems sharpened.

F.W. Harris developed theory of batch quantities in production and purchase. Walter Schewart developed procedures for using statistical thinking in process control. He created methods for determining when to change machine setups based on the measurements of samples taken at randome intervals. Hawthorne studies became another landmark development in manufacturing management. They brought out the importance of psychological variables in improving or decreasing productivity of operators. Unfortunately, the proponents of this line of thought have not integrated their conclusions with the ideas of scientific management appropriately. They chose to attack themes of scientific management. Manufacturing management might have had a different state today, if scientific management movement that had engineering foundations and human relations school of thought that had psychology as its foundation were appropriately integrated by human relations school.

Hawthorne studies became another landmark development in manufacturing management. They brought out the importance of psychological variables in improving or decreasing productivity of operators. Unfortunately, the proponents of this line of thought have not integrated their conclusions with the ideas of scientific management appropriately. They chose to attack themes of scientific management. Manufacturing management might have had a different state today, if scientific management movement that had engineering foundations and human relations school of thought that had psychology as its foundation were appropriately integrated by human relations school.

Development of operations research (OR) helped manufacturing managers to understand and optimize their systems better. Study of operations research became a part of studies of manufacturing managers.  Use of computers was started in recording store related transactions and data and it was extended to shopfloor transaction data. The use was further extended to calculation of batch quantities and preparation of  loading sheets and schedules.

In 1970s, scholars in USA recognized that Japanese had used their manufacturing management philosophies, strategies and techniqes as a strategic capability to win market shares in global markets. A new era of manufacturing strategy thought developed in manufacturing management.  Automation increased in factories. With this multiskilling of operators came into picture as now operators have more time and can operate more machines. As group layout became more popular, an operator was required to operate different machines which were in series. Total quality management, total productive maintenance, total cost management became the strategies. JIT or lean systems became the best practice production systems. While improvement everywhere reached its zenith, the important idea that it is improvement in bottleneck that has the most value was highlighted by Goldratt in the name of 'Theory of Constraints.'

Many new technologies came into existence and were adopted into manucturing processes. The existing ideas regardng technology adoption did not emphasize the suboptimal use of technology. The full power of technology was not being put to use by many. Theory of BPR brought this into focus and helped systems become more productive by utilizing the power and potential of the new technologies more. Ability to look at bigger and bigger systems using OR models and system dynamics models and the ability to access data anywhere using internet based data communication systems made coordination across distributed national and global facilities. This led to the development of theory of supply chain wherein information can be made visible to anybody and optimization can be done from the point of origin or raw materials to its dumping point. Manufacturing facilities are now a part of supply chains wherein information is available to both suppliers and potential customers in real time and purchasing is done through electronic orders. In a century, manufacturing management theory and pratice developed immensely.

Chase, Richard, B., F. Robert Jacobs, Nicholas J. Aquilano , Operations Management, 11th Edition, McGraw-Hill, New York, 2006.
Krajewski, Lee et al., Operations Management: Processes and Value Chains, 8th Edition, Prentice Hall, Upper Saddle River, 2007.


Early Books on Manufacturing Management

Factory Organization and Administration
Hugo Dimer, First Professor of Industrial Engineering, Pennsylavania State College
First edition: 1910
Third edition digital copy

Profit Making in Shop and Factory Management
Charles U. Carpenter, 1908

Shop Management
Frederick Winslow Taylor, 1911

Factory and Office Administration
Lee Galloway, 1918

Factory Management Wastes: And How to Prevent Them
James F. Whiteford, 1919

Plant Management
Dexter S. Kimball, 1919


Article part of chapter  Introduction  to Manufacturing Management

Chapter - Introduction to Manufacturing Management


Narayana Rao

All Rights Reserved

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Exported: 26 Nov 2011

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Chapter of Manufacturing Management - Knol Book

Contents of Chapter

Principles of Management – Koontz and O’Donnell

Manufacturing Management - Introduction

Manufacturing Management - Introduction - Interesting Web Pages  

Preface to Manufacturing Management - Blog Book

Preface to Manufacturing Management - Knol Book


Narayana Rao

All Rights Reserved

Version 2

Last edited: 18 Nov 2010

Exported: 26 Nov 2011

Original URL:

Study each book and seminar,
Attend every one you can, sir!
You'll find a thousand experts
--each with PART of the answer.    (O.W. Wight in the book, Production and Inventory Control: Principles and Techniques)

Digital media or electronic media products have made it possible for more experts (even in a limited way) to write their thoughts and understanding of issues and share the knowledge with rest. People in general have followed Wight's advice and are reading digital media articles.

Knol, a wiki-based article writing platform is another digital media product launched by Google to promote writing units of knowledge, knols. Number of professionals and faculty members are writing on Knol. Knol books of collections are part of efforts to bring articles or knols related to a subject together and present them to readers. Such books make accessing thousands of experts more easy for readers. Society will be benefited, if more people become more knowledgeable and use that knowledge to produce more goods and services and more importantly happiness and also preserve environment for present as well as future generations.

Robust Design

Chapter  13 Ulrich and Eppinger - Product Design and Development

Robust Design

1. Identify Control Factors,  Noise Factors, and Performance Metrics
2. Formulate an Objective Function
3. Develop an Experimental Plan
4. Run the Experiment
5. Conduct the Analysis
6. Select and Confirm Factor Setpoints


Chapter  12 Ulrich and Eppinger - Product Design and Development

Prototyping - Planning for Prototyping

1. Define the Purpose of the Prototype
2. Establish the Level of Approximation of the Prototype
3. Outline an Experimental Plan
4. Create a Schedule for Procurement, Construction and Testing

Design for Manufacturing - A Step in Product Design and Development

Chapter  11 Ulrich and Eppinger - Product Design and Development

Manufacturing cost is a key determinant of the economic success of a product. Economic success depends on the profit earned on each item sold, and how many units of the product the firm can sell.  if the price is set lower more sales can be achieved. But to maintain profit margin or profit on each item sold, cost also have to low. Design for manufacturing activity helps in lowering the cost of manufacturing by modifying the design to suit manufacturing capabilities without decreasing the quality of the product.

Design for Manufacturing

1. Estimate the Manufacturing Costs
2. Reduce the Cost of Components
3. Reduce the Cost of Assembly
4. Reduce the Costs of Supporting Production
5. Consider the Impact of DFM Decisions on other Factors


1. Estimate the Manufacturing Costs
2. Reduce the Cost of Components

Understand the Process Constraints and Cost Drivers
Redesign Components to Eliminate Processing Steps
Choose the Appropriate Economic Scale for the Part Process
Standardize Components and Processes
Adhere to "Black Box" Component Procurement. Allow the supplier to design the product based functional specification.

3. Reduce the Cost of Assembly

Integrate Parts
Maximize Ease of Assembly
Consider Customer Assembly

4. Reduce the Costs of Supporting Production

Minimize Systemic Complexity
Error Proofing (Pokayoke)

5. Consider the Impact of DFM Decisions on other Factors