Learning Outcomes of FHH3510 Forest Products Industrial Operation Analysis

Learning outcomes FHH3510

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Learning Outcomes of FHH3510 Forest Products Industrial Operation Analysis by Mind Map: Learning Outcomes of FHH3510 Forest Products Industrial Operation Analysis

1. 3) Plant layout

1.1. a) When

1.1.1. When first starting the business, when moving to a new location, when decides to purchase new machinery.

1.2. b) Why

1.2.1. Poorly designed layout could result in increased number of accidents, decreased inventory space, excessive stock in process at the facility, labor anxiety and discomfort, qualified workers carrying out too many simple operations, and bottlenecks.

1.2.2. To ensure a smooth flow of work, material, people and information

1.3. c) Types

1.3.1. Fixed

1.3.1.1. - The materials or major components remain in a fixed position, and workers, materials, and equipment are moved as needed. - Used when product is very bulky, heavy or fragile - Used in large construction projects

1.3.1.2. Ex : Power plants, dams, ship building, production of large aircraft and space mission rockets.

1.3.2. Process

1.3.2.1. - Process layouts are those in which equipment and workstations are arranged according to the type of process they perform. - Machines are grouped into departments or stations according to its function. - A manufacturing example of a process layout is the machine shop, which has separate departments for milling, grinding, drilling, and so on. - Used primarily in a facility producing variety of different products and each requires a different series of processing steps to be performed in a different sequence. - Require most movement of products from workstation to workstation.

1.3.2.2. Ex : Job shops, machine shops

1.3.3. Product

1.3.3.1. - To achieve a smooth and rapid flow of large volumes of products. - Equipment and manual workstations arranged to mirror the required flow of these specified products through the steps in the manufacturing process. - Assembly line is arranged in a logical order of assembly (layout design).

1.3.3.2. Ex : Door manufacturers

1.4. d) Design

1.4.1. Factors influencing

1.4.1.1. Nature of products, factory building, production process, types of machinery, maintenance, human needs, plant environment and management policies.

1.4.2. Process flow diagram

1.4.2.1. what

1.4.2.1.1. - Indicate the general flow of plant processes and equipment. - Elements that may be included are: sequence of actions, inputs and outputs, decisions that must be made, involved people, time involved at each step and/or process. - A generic tool that can be adapted for a wide variety of purposes.

1.4.2.2. when to use

1.4.2.2.1. - Develop understanding of how a process is done. - To study a process for improvement. - To communicate to others how a process is done. - Better communication is needed between people involved with the same process. - To document a process. - Planning a project.

1.4.2.3. procedure

1.4.2.3.1. - Define the process to be diagrammed. - Write its title at the top of the work surface. - Discuss and decide on the boundaries of the process. - Brainstorm the activities that take place. - Write each on a card or sticky note. - Arrange the activities in proper sequence. - Draw arrows to show the flow of the process. - Review the flowchart with others involved in the process.

1.4.3. Layout solution

1.4.3.1. - The total distance that materials must move through the plant is reduced. - A single, linear flow through the plant eliminated unstrategic traffic patterns that lead to traffic jams. - Reorganized internal spaces result in more efficient cycle time. - Process maybe performed in parallel instead of sequentially.

1.5. e) Bottlenecks

1.5.1. what

1.5.1.1. The production line process that accumulates the longest queue

1.5.1.2. In manufacturing, there is always one part of the process that is the slowest

1.5.2. How to identify

1.5.2.1. - Processing step or machine that has high wait time. - Machine that is running a full capacity while it operates and breaks down frequently. - Unskilled operator who needs training.

1.6. f) Usable software to design

1.6.1. ALDEP (Automated layout design program)

1.6.2. CORELAP (Computerized related allocation of facilities technique)

1.6.3. CALP (Computer Aided layout planning)

2. 4) Demand Forecasting

2.1. a) Definition

2.1.1. - Process of predicting the future and crucial to any suppliers, manufacturer, or retailer. - Marketing and production are two functional areas that make the most of forecasting method. - Production department used sales forecast from marketing department for operations planning. - Forecasting product demand for monthly scheduling are done.

2.2. b) Considerations

2.2.1. - Specifying the objective. - Determining the time perspective. - Making choice of appropriate technique. - Collection of data. - Estimation and interpretation of results. - Evaluation of the forecasts.

2.3. c) Time horizon

2.3.1. Short

2.3.1.1. Measured in days or weeks

2.3.1.2. Ex : inventory management

2.3.2. Intermediate

2.3.2.1. Measured in weeks or months

2.3.2.2. Ex : Sales pattern, requirement and availability of workers

2.3.3. Long

2.3.3.1. Firm's manufacturing strategies

2.3.3.2. Ex : Downsizing, construction of new facilities.

2.4. d) Techniques

2.4.1. Qualitative

2.4.1.1. Hierarchical methods

2.4.1.1.1. - Called as “sales force polling”, salesmen are required to estimate expected sales in their respective territories and sections. - Then sales manager of a region could take all individual forecast to produce aggregate regional forecast. - Called as “bottom-up” forecasting.

2.4.1.2. Expert opinion

2.4.1.2.1. - To ask experts in the fields to provide estimates. - Useful for new products. - Develop a forecast from the results of interview or require executive to meet as groups and come to a consensus.

2.4.1.3. Delphi method

2.4.1.3.1. - An effort to arrive at a consensus about expected level of demand by questioning a group of experts. - The results are compiled and a summary of the result is returned to the expert. - Repeat until an overall group consensus is reached. - Response received and analyzed by independent body.

2.4.1.4. Surveys

2.4.1.4.1. - Also known as opinion surveys. - Interviews or questionnaires are used. - Signal the future trends and shifting preference patterns. - Effective in forecasting market share, product redesign, product repackaging, setting prices.

2.4.2. Quantitative

2.4.2.1. Moving averages

2.4.2.1.1. - Known as rolling average, moving mean, or running average. - Analyze a series of averages of different subset of numbers from a larger set of data including opening and closing prices/demand, highest and lowest prices, and interval of periods. - “Moving” because averaging the information across a period. - Used with time series data to smooth out short term fluctuation and highlight longer-term trends or cycles. - Will not work well if there is strong trend or tendency toward growth or decline, seasonality factor.

2.4.2.1.2. The longer the periods, the smoother the data. The shorter the periods, the data is responsive and move to sale level to previous sale.

2.4.2.2. Weighted moving averages

2.4.2.2.1. More recent values in a series are given more weight in computing the forecast.

2.4.2.2.2. Able to give more importance to what happened recently, without losing the impact of the past.

2.4.2.2.3. The higher the importance given to recent data, the more pick up of the declining trend in the forecast.

2.4.2.2.4. How choose weight

2.4.2.3. Exponential smoothing

2.4.2.3.1. Provides an exponentially weighted moving average of all previously observed values.

2.4.2.3.2. The smoothing constant, 𝛼 (0.0 - 1.0), reflects the weight given to the most recent demand data.

2.4.2.3.3. The higher α is, the more sensitive the forecast will be to changes in recent demand, and the smoothing will be less.

2.4.2.3.4. As α approaches zero, the forecast will react and adjust more slowly to differences between the actual demand and the forecasted demand (smoothing data).

2.4.2.3.5. Determination of α is usually judgmental and subjective and is often based on trial-and-error experimentation.

2.4.2.4. Linear regression

2.4.2.4.1. - Fitting a straight line to a trend data. - Estimating the linear trend in a time series

2.4.2.4.2. Correlation coefficient (r)

2.4.2.4.3. Coefficient of determination (r-squared)

3. 5) Linear Programming

3.1. a) What

3.1.1. - Mathematical technique for finding optimal solution to problems that can be expressed using linear equations and linear inequalities. - Also known as linear optimization.

3.1.2. Linear model

3.1.2.1. Linear functions - All terms consist of single continuous-values variable. - Each variable is raised to power of 1.

3.2. b) Consists of

3.2.1. Variables

3.2.1.1. - A set of quantities that need to be determined to solve the problem. - Represent the amount of a resource to use or the level of some activity.

3.2.2. Linear objective function

3.2.2.1. - Represented by mathematical function of the variables.

3.2.2.2. Two most typical forms of objective functions:

3.2.2.2.1. maximize f(x)

3.2.2.2.2. minimize f(x)

3.2.3. Linear constraints

3.2.3.1. Mathematical equation or inequality that represents a restriction due to a resource or technological limitation. f (x)≥ b or f (x) ≤ b or f (x) = b

3.2.4. Linear equation

3.2.4.1. a0 + a1 x1 + a2 x2 + a3 x3 + . . . + an xn = 0

3.2.4.1.1. The a’s are called the coefficients of the equation, also called parameters.

3.2.4.1.2. - The x’s are called the variables of the equation, take on a range of values within the limits defined by the constraints.

3.3. c) Application

3.3.1. Scheduling of personnel. E.g., number of employee per shift.

3.3.2. Inventory control and production planning. E.g., how many items to produce each time period so as to satisfy customer demand, storage limitation.

3.3.3. Blending problems including cattle feed, petroleum products to produce different grades of gasoline. Transportation. E.g., Best route to deliver goods.

3.3.4. Forest management planning. E.g., Timber allocation model.

3.4. d) Steps

3.4.1. Define the decision variables

3.4.1.1. - Directly controllable. - Often referred to as control variable.

3.4.2. Formulate the objective function

3.4.2.1. Desire of the decision maker and may typically one of the following: - Maximize profit - Minimize cost - Minimize overtime

3.4.3. Formulate the constraints

3.4.3.1. Result of a resource or technological limitations (e.g., limited raw material, limited budget, limited time, limited personnel, limited skills)

3.4.4. Non-negativity constraints

3.4.4.1. - For technical reasons, the variables of linear programs must always take non-negative values. - Must be greater than or equal to zero).

3.5. Key steps

3.5.1. Formulate

3.5.1.1. - Process of translating a real-world problem into a linear program. - Express a real-world problem as a mathematical problem).

3.5.2. Solve

3.5.2.1. - A computer program can be used to solve the problem

3.5.3. Interpret

3.5.3.1. - Interpreting the solution is the final step. - The mathematical solution is translated back to the real world

3.6. e) Answer report

3.6.1. Optimal values of the variables

3.6.1.1. The “variable cell” in the Answer Report gives the optimal values of the variables under the heading “Final Value.”

3.6.2. The optimal objective function value

3.6.2.1. The “objective cell” in the Answer Report gives the value of the objective function.

3.6.3. Slack or surplus values

3.6.3.1. The “constraints” in the Answer Report lists the slack or surplus values reported for each constraint.

3.6.3.2. Slack

3.6.3.2.1. - Applies to less than or equal constraints. - Amount of a resource, as represented by a less-than-or-equal constraint, that is not being used.

3.6.3.3. Surplus

3.6.3.3.1. - Applies to greater than or equal constraints. - When a greater-than-or-equal constraint is not binding, then the surplus is the extra amount over the constraint that is being produced or utilized.

3.7. f) Sensitivity report

3.7.1. Changing the objective function for a variable

3.7.1.1. - One of the info from the variable cells table is on the impact of changes to the objective function coefficient on the optimal solution. - To illustrate this, vary the coefficient of variable and see how the optimal value will change.

3.7.2. Reduced costs

3.7.2.1. Another info from the “variable cells” in the Sensitivity Report gives the reduced cost values associated with each variable.

3.7.2.2. The value indicates how much the coefficient on the corresponding variable must be “improved” before the value of the variable will be positive in the optimal solution.

3.7.2.2.1. If minimization problem, “improved” means “reduced.”

3.7.2.2.2. If maximization problem, “improved” means “increased.”

3.7.2.3. The value is only non-zero when the optimal value of a variable is zero.

3.7.2.4. The units of the values are the same as the units of the corresponding objective function coefficients

3.7.2.5. Since both variable values are positive, the reduced costs values also zero.

3.7.3. Shadow (dual) prices

3.7.3.1. The Sensitivity Report gives the shadow price for each constraint.

3.7.3.2. The shadow price gives the “improvement” in the objective function if the constraint is relaxed by one unit.

3.7.3.2.1. If less-than-or-equal constraint, such as a resource constraint, the dual price gives the value (in terms of the objective function) of having one more unit of the resource represented by that constraint.

3.7.3.2.2. In the case of a greater-than-or-equal constraint, such as a minimum production level constraint, the dual price gives the cost (in terms of the objective function) of meeting the last unit of the minimum production target.

3.7.3.3. Only non-zero when a constraint is binding.

3.7.3.4. The units are the units of the objective function divided by the units of the constraint.

3.8. g) Feasibility and optimality

3.8.1. The solution is a set of values for each variable that: - consistent with the constraints (feasible) - result in the best possible value of the objective function (optimal).

3.8.2. 2 Possibilities if LP not have solution

3.8.2.1. - There are no solutions that are consistent with all the constraints - One or more of the constraints must have to be relaxed (loosened).

3.8.2.2. - The optimal solution is infinitely large in the case of a maximization problem. - The problem probably has not been well formulated since few.

4. 1) Production and Operation Management Concept

4.1. a) Management

4.1.1. Planning, organizing, actuating, and controlling to determine and achieved the desired objectives with the use of human beings and other resources

4.2. b) Operation

4.2.1. daily actions / task / activities necessary for the production system to work

4.3. c) Production

4.3.1. step-by-step conversion of one form of material into another form through chemical or mechanical process to create or enhance the utility of the product to the user

4.4. d) Production System

4.4.1. to transform an input into a desired output by means of a process (the transformation process) and resources.

4.4.2. 4 elements

4.4.2.1. Input (e.g., flour, sugar)

4.4.2.2. Resources (e.g., oven, workers)

4.4.2.3. Production Process (e.g., Fabrication,Heating)

4.4.2.4. Output (e.g., Breads,Cakes)

4.4.3. Classification

4.4.3.1. Job Shop

4.4.3.1.1. - High variety of products - Typically make single product at a time (cause low volume production) - Use of general purpose machines and facilities. - Highly skilled operators who can take up each job as a challenge because of uniqueness. - Large inventory of materials, tools, parts.

4.4.3.1.2. Ex : Furniture , door, cabinet (Special order, Custom made)

4.4.3.2. Batch

4.4.3.2.1. - Shorter production runs. - Plant and machinery are flexible. - Plant and machinery set up is used for the production of item in a batch and change of set up is required for processing the next batch.

4.4.3.2.2. Ex : Bakeries, pharmaceutical ingredients, paints and adhesive, clothing.

4.4.3.3. Mass

4.4.3.3.1. - Standardization of product and process sequence. - Dedicated special purpose machines having higher production capacities. - Large volume of products. - Shorter cycle time of production. - Lower in process inventory.

4.4.3.3.2. Ex : Auto-parts, machines

4.4.3.4. Continuous

4.4.3.4.1. - Dedicated plant and equipment with zero flexibility. - Material handling is fully automated. - Process follows a predetermined sequence of operations. - Component materials cannot be readily identified with final product. - Planning and scheduling is a routine action.

4.4.3.4.2. Ex : Paper and chemical business.

4.5. e) Production and Operation Management

4.5.1. Manufacturing management -> production management -> Operation Management (responsible for systems which create goods or services, or both.)

4.5.2. Operation Managers

4.5.2.1. Planning, Organizing, Staffing, Leading, Controlling

4.5.3. Decision Area

4.5.3.1. - Location strategy - Plant layout strategy - Forecasting - Process and capacity design - Inventory management - Scheduling and allocation of resources - Human resource and job design - Managing quality - Maintenance

4.5.4. Importance

4.5.4.1. - Reduce the cost of products and services by being efficient - Increase revenue through increases customer satisfaction in producing quality goods and services - Reduce the amount of investment necessary to produce the goods and services.

5. 2) Plant Location

5.1. a) Why

5.1.1. - Expanding an existing facility. - Shutting down one location and moving to another. - Adding new locations while retaining existing facilities - Maintaining the status quo

5.2. b) Relocation Factors

5.2.1. Market-related

5.2.1.1. Competitors

5.2.1.1.1. Near or Avoid

5.2.1.2. Demand

5.2.1.2.1. - Determine where goods are most likely to be sold. - Determined based on centroid or weighted center of products demanded.

5.2.2. Tangible cost

5.2.2.1. Transportation

5.2.2.1.1. Minimum-cost

5.2.2.1.2. International

5.2.2.2. Raw material supplies

5.2.2.2.1. - Sufficient and sustainable - Less competition for same raw material

5.2.2.3. Labor availability

5.2.2.3.1. - Skilled or unskilled labor. - Cheap labor rates for labor-intensive companies.

5.2.2.4. Site and construction

5.2.2.4.1. - Cost of purchasing. - Enough land for log yard or source of water.

5.2.2.5. Taxes

5.2.3. Intangible

5.2.3.1. Political environment stability

5.2.3.2. Zoning and legal consideration

5.2.3.2.1. - Types of business operate in certain areas are in controlled. - Future diversification of companies might be limited.

5.2.3.3. Quality of Life

5.2.3.3.1. Cost of living, high crime rate, nearness to amenities.

5.3. c) Location Decision

5.3.1. Location Evaluation Methods

5.3.1.1. Transportation model

5.3.1.1.1. Linear Programming

5.3.1.1.2. Geographical Information System

5.3.1.2. Factor-rating

5.3.1.2.1. - Involves qualitative and quantitative inputs, and Evaluates alternatives based on comparison after establishing a composite value for each alternative. - Wide variety of factors can be included in the analysis

5.3.1.2.2. Steps

5.3.1.3. Center of gravity

5.3.1.3.1. - Quantitative method for locating a facility at the center of movement in a geographic area based on weight and distance. - Indicates the ideal location in the grid-map which ensure the minimization of weighted distances traveled on the whole. - Involves the use of a visual map and a coordinate system.

6. 6) Lean Manufacturing

6.1. a) What

6.1.1. - A systematic approach to achieve shortest possible cycle by eliminating the process waste through continuous improvement. - Manufacturing without waste and focuses on flow - Production of goods using less of everything compared to traditional mass production e.g., less waste, human effort, manufacturing space, investment in tools, inventory, and engineering time to develop a new product.

6.2. b) Push vs Pull

6.2.1. Push

6.2.1.1. - Traditional “batch-and-queue” manufacturing method. - Manufacturing as much product in as little time as possible - “push” the product to the next operation. - Manufactures and distributes products based on market forecasts that often are out dated or wrong by the time the product is delivered.

6.2.2. Pull (Kanban)

6.2.2.1. - Pulling the products through the manufacturing process. - Starts with the customer, nothing is manufactured until the customer orders it. - The next processing center can be thought of as an internal customer. - Parts are not passed on from one processing station until the next internal customer “pulls” them.

6.3. c) Waste

6.3.1. What

6.3.1.1. - Anything that happens to a product that does not add value and the value is defined by the customer. - Products being stored, inspected or delayed, products waiting in queues, and defective products do not add value

6.3.2. Types

6.3.2.1. Overproduction : Producing more/sooner than the Internal or External customer needs.

6.3.2.2. Waiting : Long periods of inactivity for people, information, machinery or materials.

6.3.2.3. Transportation : Excessive movement of people, information or materials.

6.3.2.4. In appropriate processing : Using the wrong set of tools, procedures or systems.

6.3.2.5. Unnecessary Inventory : Excessive storage and delay of information or products.

6.3.2.6. Motion : people or equipment moving or walking more than is required to perform the processing.

6.3.2.7. Defects : Frequent errors in paper work, product quality problems.

6.4. d) Lean

6.4.1. Principle

6.4.1.1. Specify value : Specify value from the standpoint of the end customer by product family.

6.4.1.2. Identify the value stream : Identify all the steps in the value stream for each product family, eliminating whenever possible those steps that do not create value.

6.4.1.3. Create flow : Make the value-creating steps occur in tight sequence so the product will flow smoothly toward the customer.

6.4.1.4. Let customer pull product through the value stream: Make only what the customer has ordered.

6.4.1.5. Seek perfection : begin the process again and continue it until a state of perfection is reached in which perfect value is created with no waste.

6.4.2. Tools

6.4.2.1. Poka-Yoke

6.4.2.1.1. - Japanese term means “Mistake proofing”. - Techniques/device to prevent defects or error from occur. - Drive defects out of products and processes or human error which ultimately can improve quality and reliability. - Example: Wrong part used in the process, measurement error etc.

6.4.2.1.2. Types

6.4.2.2. 5s Visual Workplace

6.4.2.2.1. What

6.4.2.2.2. Types

6.4.2.3. Just in Time

6.4.2.3.1. What

6.4.2.3.2. Benefits

6.4.3. Economical benefits

6.4.3.1. Reduction of Inventory : Less space necessary to hold inventory.

6.4.3.2. Reduced Waste : Decreased Production Cost.

6.4.3.3. Increased market share : Able to provide what the customer wants quickly.

6.4.3.4. Increased competitive advantage : - Faster response to the customer - Lower Cost - Higher Quality

6.4.4. Practices in forest product industry

6.4.4.1. - Not widespread in the forest products industry, perhaps because the sector traditionally has been conservative in adapting new technologies and methods.

6.4.4.2. Some forest products manufacturing companies are embracing a lean manufacturing system as to compete successfully in the global market like in U.S and Europe.

6.4.4.3. MTIB is currently undertaking a lean management program for the wood-based products manufacturer in Peninsular Malaysia.

6.4.4.4. Effort to reduce waste and foreign labor dependency so that the manufacturing process flow can be optimized and to reduce production costs while increase productivity.