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| an older name for lean systems |
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| Toyota Production System (TPS) |
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| another name for lean systems, specifically as implemented at Toyota |
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| a philosophy of minimizing the resources needed for processes |
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Only the good/services that customers want As quickly as customers want With only features customers want With perfect quality In minimum possible lead time Without waste With occupational development of workers |
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| Principle 1: Specify Value |
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Customers determine value Suppliers must provide products/services with customer desired Outcomes Product features Functionality Capabilities Anything that doesn’t add value is waste! |
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| Principle 2: Identify Value Stream |
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Waste is a symptom of a problem, and does not add value Overproduction: processing more than needed Waiting: resources waiting for work/materials Transportation: units moved unnecessarily Processing: excessive or unnecessary steps Inventory: units waiting for processing or delivery Motion: unnecessary or excessive resource activity Defects: scrap, rework or correction |
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| Principle 3 : Make Value Flow |
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| Inventory hides problems and slows flow |
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| Principle 4: Customers Pull Value |
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Pull System: processes are activated by actual, not forecasted demand Customers get what they want when they want where they want |
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| Principle 5: Pursue Perfection |
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Lean System Culture: places a high value on respect for people Acceptance: agree to goals, veterans teach new employees Flexibility: responsive pull systems Teams: cross-functional & cross-organizational Employee empowerment: employees work to attack waste Manage with data: objective over subjective Waste as a symptom: attack root cause Goals are met: set realistic, achievable goals Standardization: reduces variation, simplifies problem solving Process focus: process change for outcome change |
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| Lean Tools and Techniques:Facilities and Resources |
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| Total Productive Maintenance (TPM), Group Technology, Focused Factories |
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| Total Productive Maintenance (TPM) |
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| bring together resources to process a family of items |
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| processes designed to satisfy specific customer segment |
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| Lean Tools and Techniques:Scheduling and Control |
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| Takt Time, Kanban (Pull), Mixed Model (heijunka), Set-up reduction, Statistical process control (SPC), Visual control |
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| synchronizing output rate with demand rate |
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| output generated in response to actual demand |
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| build smaller quantities more frequently |
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| shorter, easier change- over leads to smaller batches |
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| Statistical process control (SPC) |
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| use of statistical tools to monitor processes |
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| performance and problems easily, immediately visible |
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| Setup Reduction: Single Minute Exchange of Dies |
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Stage 1: Separate internal and external setups Stage 2: Convert internal setups to external setups Stage 3: Streamline all activities in a setup |
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| Lean Tools and Techniques:Continuous Improvement |
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| Quality at the source, Kaizen Events, Process analysis/Value stream mapping, Poka-Yoke, 5-S, Simplification/Standardization |
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| eliminating defects at their origination points (jidoka, andons, stop and fix) |
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| short-term, cross-functional focused, intense process improvement |
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| Process analysis/Value stream mapping |
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| graphical analysis flow through a process |
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| redesign so mistakes are impossible or immediately detectable |
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| effective housekeeping (sort, straighten, scrub, systematize, standardize) |
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| Simplification/Standardization |
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| removing non-value add steps, making processes exactly repeatable |
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| Application of Lean across the supply chain |
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Purchase for lowest total cost (not price) Geographically close partners Fewer suppliers Focus on root cause Work with, not against, suppliers |
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| Application of Lean with product innovation (lean design) |
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Exactly meet customer needs Support corporate strategy Reduce opportunities of waste |
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| Types of events causing problems for lean supply chains |
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| Legal/political, operational/technological, social, natural/hazard, economy/competition |
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| Reducing product design waste |
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Complexity: few, simple processes Precision: capability to attain specifications Variability: attainable specifications Sensitivity: not easily damaged Immaturity: tested technology Danger: customers & environment are safe High skill: ease for workers and customer |
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| both forecasting and managing customer demand to reach operational and financial goals |
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| predicting future customer demand |
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| influencing either pattern or consistency of demand |
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patterns of demand over time (stable, seasonal, trend, step change) |
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| relationship of past and current demand |
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| “unexplained” component of demand |
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| Judgment Based Forecasting (types) |
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| Grassroots, Executive Judgment, Historical Analogy, Marketing Research, Delphi Method |
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| input from those close to products or customers |
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| input from those with experience |
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| assume past demand is a good predictor of future demand |
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| examine patterns of current customers |
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| input for panel of experts |
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| Statistical Based Forecasting (Types) |
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| Time Series Analysis, Causal Studies, Simulation models, Moving Average, Weighted Moving Average, Exponential Smoothing, Regression Analysis, Simulation Models, Focused Forecasting |
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| uses historical data arranged in order of occurrence |
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| search for cause and effect relationships among variables |
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| create representations of previous events to evaluate future outcomes |
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| simple average of demand from some number of past periods |
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| assigns different weights to each period’s demand based upon its importance |
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| a moving average approach that put less weight on further back in time data |
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| weight given to most recent demand |
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| adjustment factor to account for seasonal changes or cycles in demand. A ‘season’ can be any time period. |
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| period actual demand / average period demand |
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| Average of SI data for given time frame |
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| fits an equation to a set of data |
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| sophisticated techniques that allow for the evaluation of multiple business scenarios |
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| combination of computer simulation and input from knowledgeable individuals |
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| measure of how closely forecast aligns with demand |
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| tendency to over or under predict future demand (forecast error) |
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| Mean Absolute Deviation (MAD) |
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| average of forecast errors, irrespective of direct |
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| Mean Absolute Percentage Error (MAPE) |
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| the MAD adjusted to measure how large errors are relative to the actual demand quantities |
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| ratio of running forecast error to MAD |
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| Forecast Process Performance |
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Short term forecasts are more accurate than long term forecasts. Aggregate forecasts are more accurate than detailed forecasts. Information from more sources yields a more accurate forecast. |
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Fluctuating customer demand cause operational inefficiencies, such as: Need for extra capacity resources, Backlog, Customer dissatisfaction, System buffering (safety stock, safety lead time, capacity cushions, etc.). |
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Use pricing, promotions or incentives to influence timing or quantity of demand. Manage timing of order fulfillment. Encourage shifting to alternate products. |
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| Improving Planning Management |
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| improving information accuracy and timeliness, redesigning the product, reducing lead time, collaborating and sharing information |
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| Collaborative, planning, forecasting and replenishment (CPFR) |
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supply chain partners share forecast, and demand and resource plans to reduce risk. Market Planning: changes to products, locations, pricing and promotions Demand and resource planning: forecasting. Execution: order fulfillment. Analysis: data on key performance metrics. |
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| Sales and Operations Planning (S&OP) |
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process for integrating marketing and operations plan to develop a tactical plan Attempt to balance supply and demand |
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-Finance: High ROI, Maximize return, Minimize risk, High contribution customers -Marketing/sales: Aggregate planning, Many product variations, Fast response, high service, Maximize revenue -Operations: Detail planning, Fewer products, Long, stable production runs, Maximize output, minimize cost, Reduce variance, maintain ‘up-time’, Efficient grouping of supply & demand |
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| Quantitative benefits: Sales & Operations Planning |
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Improved forecast accuracy Higher customer service More stable supply Better new product introduction |
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| Qualitative benefits Sales & Operations Planning |
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Better organizational teamwork Faster and better aligned decision making Greater accountability for performance Better business visibility |
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| Aggregate Production Planning Costs |
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| Aggregate Production Planning, Holding Inventory, Overtime, Hiring, Fire/Layoff |
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| Aggregate Production Planning |
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| balances production, inventory, resources and demand |
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| average labor and benefits |
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| working more hours than standard |
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| finding, acquiring and training new employees |
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| expediting supply, lost good-will |
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| unit cost and loss of control |
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| produce at a constant rate, use changing inventory levels to buffer supply and demand |
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| Aggregate Planning Strategies |
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change production to match demand, inventory remains relatively stable and low. 1.Produce everything in house, vary the workforce level 2.Produce everything in house, workforce level to meet lowest demand period, use overtime for higher demand 3.Produce everything in house, workforce level to meet lowest demand period, use subcontractor to produce higher demand |
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| combination of level and chase strategies |
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adjusting prices in response to demand levels Services can not create inventory to buffer demand Modify prices to encourage customers to purchase for service at supplier desired times Goal is to maximize revenue and profit |
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