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ACCU BEKAS: Februari 2009


Senin, 23 Februari 2009

Visual Control

The intent of a visual factory is that the whole workplace is set-up with signs, labels, color-coded markings, etc. such that anyone unfamiliar with the process can, in a matter of minutes, know what is going on, understand the process, and know what is being done correctly and what is out of place.
There are two types of application in visual factory: displays and controls.
A visual display relates information and data to employees in the area. For example, charts showing the monthly revenues of the company or a graphic depicting a certain type of quality issue that group members should be aware of.
A visual control is intended to actually control or guide the action of the group members. Examples of controls are readily apparent in society: stop signs, handicap parking signs, no smoking signs, etc.
This is in contrast to previous workplace rules, which dictated that performance data should be retained as "management secrets", for the sole consumption of managers who knew what do with the numbers.
Visual controls describe workplace safety, production throughput, material flow, quality metrics, or other information.
The most important benefit of a visual factory is that it shows when something is out of place or missing.
Visual displays and controls help keep things running as efficiently as they were designed to run. The efficient design of the production process that results from lean manufacturing application carries with it a set of assumptions. The process will be as successful as it was designed to be as long as the assumptions hold true. A factory with expansive visual display and control applications will allow employees to immediately know when one of the assumptions has not held true.
Audio signals in the factory are also very important because they signal malfunctioning equipment, sound warnings before the start of machine operation, or other useful information.
Visual management is an important support for cellular manufacturing. Visual management techniques express information in a way that can be understood quickly by everyone.
Sharing information through visual tools helps keep production running smoothly and safely. Shop floor teams are often involved in devising and implementing these tools through 5S and other improvement activities.
Visual information can also help prevent mistakes. Color coding is a form of visual display often used to prevent errors. Shaded "pie slices" on a dial gauge tell the viewer instantly when the needle is out of the safe range. Matching color marks is another approach that can help people use the right tool or assemble the right part.
color-coded pipes and wires
painted floor areas for good stock, scrap, trash, etc.
shadow boards for parts and tools
indicator lights
workgroup display boards with charts, metrics, procedures, etc.
production status boards
direction of flow indicators


Minggu, 22 Februari 2009


U.S. manufacturers have always searched for efficiency strategies that help reduce costs, improve output, establish competitive position, and increase market share. Early process oriented, mass production manufacturing methods common before World War II shifted afterwards to the results-oriented, output-focused, production systems that control most of today's manufacturing businesses.

Japanese manufacturers re-building after the Second World War were facing declining human, material, and financial resources. The problems they faced in manufacturing were vastly different from their Western counterparts. These circumstances led to the development of new, lower cost, manufacturing practices. Early Japanese leaders such as the Toyota Motor Company's Eiji Toyoda, Taiichi Ohno, and Shingeo Shingo developed a disciplined, process-focused production system now known as the "Toyota Production System", or "lean production." The objective of this system was to minimize the consumption of resources that added no value to a product.

The "lean manufacturing" concept was popularized in American factories in large part by the Massachusetts Institute of Technology study of the movement from mass production toward production as described in The Machine That Changed the World, (Womack, Jones & Roos, 1990), which discussed the significant performance gap between Western and Japanese automotive industries. This book described the important elements accounting for superior performance as lean production. The term "lean" was used because Japanese business methods used less human effort, capital investment, floor space, materials, and time in all aspects of operations. The resulting competition among U.S. and Japanese automakers over the last 25 years has lead to the adoption of these principles within all U.S. manufacturing businesses.


Lean Manufacturing can be defined as:

"A systematic approach to identifying and eliminating waste (non-value-added activities) through continuous improvement by flowing the product at the pull of the customer in pursuit of perfection."


In lean production, the value of a product is defined solely by the customer. The product must meet the customer's needs at both a specific time and price. The thousands of mundane and sophisticated things that manufacturers do to deliver a product are generally of little interest to customers. To view value from the eyes of the customer requires most companies to undergo comprehensive analysis of all their business processes. Identifying the value in lean production means to understand all the activities required to produce a specific product, and then to optimize the whole process from the view of the customer. This viewpoint is critically important because it helps identify activities that clearly add value, activities that add no value but cannot be avoided, and activities that add no value and can be avoided.


The transition to a lean environment does not occur overnight. A continuous improvement mentality is necessary to reach your company's goals. The term "continuous improvement" means incremental improvement of products, processes, or services over time, with the goal of reducing waste to improve workplace functionality, customer service, or product performance (Suzaki, 1987). Continuous improvement principles, as practiced by the most devoted manufacturers, result in astonishing improvements in performance that competitors find nearly impossible to achieve.

Lean production, applied correctly, results in the ability of an organization to learn. As in any organization, mistakes will always be made. However, mistakes are not usually repeated because this is a form of waste that the lean production philosophy and its methods seek to eliminate.


A lean manufacturing enterprise thinks more about its customers than it does about running machines fast to absorb labor and overhead. Ensuring customer input and feedback assures quality and customer satisfaction, all of which support sales.


The concept of perfection in lean production means that there are endless opportunities for improving the utilization of all types of assets. The systematic elimination of waste will reduce the costs of operating the extended enterprise and fulfills customer's desire for maximum value at the lowest price. While perfection may never be achieved, its pursuit is a goal worth striving for because it helps maintain constant vigilance against wasteful practices.


The aim of Lean Manufacturing is the elimination of waste in every area of production including customer relations, product design, supplier networks, and factory management. Its goal is to incorporate less human effort, less inventory, less time to develop products, and less space to become highly responsive to customer demand while producing top quality products in the most efficient and economical manner possible.

Essentially, a "waste" is anything that the customer is not willing to pay for. Typically the types of waste considered in a lean manufacturing system include:

Overproduction: to produce more than demanded or produce it before it is needed. It is visible as storage of material. It is the result of producing to speculative demand. Overproduction means making more than is required by the next process, making earlier than is required by the next process, or making faster than is required by the next process. Causes for overproduction waste include:

  • Just-in-case logic

  • Misuse of automation

  • Long process setup

  • Unlevel scheduling

  • Unbalanced work load

  • Over engineered

  • Redundant inspections

Waiting: for a machine to process should be eliminated. The principle is to maximize the utilization/efficiency of the worker instead of maximizing the utilization of the machines. Causes of waiting waste include:

  • Unbalanced work load

  • Unplanned maintenance

  • Long process set-up times

  • Misuses of automation

  • Upstream quality problems

  • Unlevel scheduling

Inventory or Work in Process (WIP): is material between operations due to large lot production or processes with long cycle times. Causes of excess inventory include:

  • Protecting the company from inefficiencies and unexpected problems

  • Product complexity

  • Unleveled scheduling

  • Poor market forecast

  • Unbalanced workload

  • Unreliable shipments by suppliers

  • Misunderstood communications

  • Reward systems

Processing waste: should be minimized by asking why a specific processing step is needed and why a specific product is produced. All unnecessary processing steps should be eliminated. Causes for processing waste include:

  • Product changes without process changes

  • Just-in-case logic

  • True customer requirements undefined

  • Over processing to accommodate downtime

  • Lack of communications

  • Redundant approvals

  • Extra copies/excessive information

Transportation: does not add any value to the product. Instead of improving the transportation, it should be minimized or eliminated (e.g. forming cells). Causes of transportation waste includes:

  • Poor plant layout

  • Poor understanding of the process flow for production

  • Large batch sizes, long lead times, and large storage areas

Motion: of the workers, machines, and transport (e.g. due to the inappropriate location of tools and parts) is waste. Instead of automating wasted motion, the operation itself should be improved. Causes of motion waste include:

  • Poor people/machine effectiveness

  • Inconsistent work methods

  • Unfavorable facility or cell layout

  • Poor workplace organization and housekeeping

  • Extra "busy" movements while waiting

Making defective products: is pure waste. Prevent the occurrence of defects instead of finding and repairing defects. Causes of processing waste include:

  • Weak process control

  • Poor quality

  • Unbalanced inventory level

  • Deficient planned maintenance

  • Inadequate education/training/work instructions

  • Product design

  • Customer needs not understood

Underutilizing people: not taking advantage of people's abilities. Causes of people waste include:

  • Old guard thinking, politics, the business culture

  • Poor hiring practices

  • Low or no investment in training

  • Low pay, high turnover strategy

Nearly every waste in the production process can fit into at least one of these categories. Those that understand the concept deeply view waste as the singular enemy that greatly limits business performance and threatens prosperity unless it is relentlessly eliminated over time. Lean manufacturing is an approach that eliminates waste by reducing costs in the overall production process, in operations within that process, and in the utilization of production labor. The focus is on making the entire process flow, not the improvement of one or more individual operations.


  • Elimination of waste

  • Equipment reliability

  • Process capability

  • Continuous flow

  • Material flows one part at a time

  • Less inventory required throughout the production process, raw material, WIP, and finished goods

  • Defect reduction

  • Lead time reduction

  • Error proofing

  • Stop the Line quality system

  • Kanban systems

  • Standard work

  • Visual management

  • In station process control

  • Level production

  • Takt Time

  • Quick Changeover

  • Teamwork

  • Point of use storage


Following are some considerations to successful lean implementation:

Prepare and motivate people

  • Widespread orientation to Continuous Improvement, quality, training and recruiting workers with appropriate skills

  • Create common understanding of need to change to lean

Employee involvement

  • Push decision making and system development down to the "lowest levels"

  • Trained and truly empowered people

Share information and manage expectations

Identify and empower champions, particularly operations managers

  • Remove roadblocks (i.e. people, layout, systems)

  • Make it both directive yet empowering

Atmosphere of experimentation

  • Tolerating mistakes, patience, etc.

  • Willingness to take risks

Installing "enlightened" and realistic performance measures, evaluation, and reward systems

  • Do away with rigid performance goals during implementation

  • Measure results and not number activities/events

  • Tie improvements, long term, to key macro level performance targets (i.e. inventory turns, quality, delivery, overall cost reductions)

The need to execute pilot projects prior to rolling culture out across the organization

  • After early wins in operations, extend across ENTIRE organization


For years manufacturers have created products in anticipation of having a market for them. Operations have traditionally been driven by sales forecasts and firms tended to stockpile inventories in case they were needed. A key difference in Lean Manufacturing is that it is based on the concept that production can and should be driven by real customer demand. Instead of producing what you hope to sell, Lean Manufacturing can produce what your customer wants...with shorter lead times. Instead of pushing product to market, it's pulled there through a system that's set up to quickly respond to customer demand.

Lean organizations are capable of producing high-quality products economically in lower volumes and bringing them to market faster than mass producers. A lean organization can make twice as much product with twice the quality and half the time and space, at half the cost, with a fraction of the normal work-in-process inventory. Lean management is about operating the most efficient and effective organization possible, with the least cost and zero waste.




Business Strategy

Product-out strategy focused on exploiting economies of scale of stable product designs and non-unique technologies

Customer focused strategy focused on identifying and exploiting shifting competitive advantage.

Customer Satisfaction

Makes what engineers want in large quantities at statistically acceptable quality levels; dispose of unused inventory at sale prices

Makes what customers want with zero defect, when they want it, and only in the quantities they order


Leadership by executive command

Leadership by vision and broad participation


Hierarchical structures that encourage following orders and discourage the flow of vital information that highlights defects, operator errors, equipment abnormalities, and organizational deficiencies.

Flat structures that encourage initiative and encourage the flow of vital information that highlights defects, operator errors, equipment abnormalities, and organizational deficiencies.

External Relations

Based on price

Based on long-term relationships

Information Management

Information-weak management based on abstract reports

Information-rich management based on visual control systems maintained by all employees


Culture of loyalty and obedience, subculture of alienation and labor strife

Harmonious culture of involvement based on long-term development of human resources


Large-scale machines, functional layout, minimal skills, long production runs, massive inventories

Human-scale machines, cell-type layout, multi-skilling, one-piece flow, zero inventories

Operational capability

Dumb tools that assume an extreme division of labor, the following of orders, and no problem solving skills

Smart tools that assume standardized work, strength in problem identification, hypothesis generation, and experimentation


Maintenance by maintenance specialists

Equipment management by production, maintenance and engineering


"Isolated genius" model, with little input from customers and little respect for production realities.

Team-based model, with high input from customers and concurrent development of product and production process design




Production schedules are based on…

Forecast — product is pushed through the facility

Customer Order — product is pulled through the facility

Products manufactured to…

Replenish finished goods inventory

Fill customer orders (immediate shipments)

Production cycle times are…



Manufacturing lot size quantities are…

Large, with large batches moving between operations; product is sent ahead of each operation

Small, and based on one-piece flow between operations

Plant and equipment layout is…

By department function

By product flow, using cells or lines for product families

Quality is assured…

Through lot sampling

100% at the production source

Workers are typically assigned…

One person per machine

With one person handling several machines

Worker empowerment is…

Low — little input into how operation is performed

High — has responsibility for identifying and implementing improvements

Inventory levels are…

High — large warehouse of finished goods, and central storeroom for in-process staging

Low — small amounts between operations, ship often

Inventory turns are…

Low — 6-9 turns pr year or less

High — 20+ turns per year

Flexibility in changing manufacturing schedules is…

Low — difficult to handle and adjust to

High — easy to adjust to and implement

Manufacturing costs are…

Rising and difficult to control

Stable/decreasing and under control


All types of manufacturers are discovering the advantages of doing a Lean analysis and applying the principles of Lean Manufacturing to their own company. Perhaps you're faced with one, or many, of these challenges:

Missed order dates

High product cost relative to the competition

Declining market share due to delivery time or cost problems

Limited capacity

If so, Lean Manufacturing can have an immediate, positive impact on your company. Through the process of implementing Lean Manufacturing you will be able to find ways to achieve a number of benefits. Results will vary, but here are some typical savings and improvements:


Manufacturing Lead Time

50 - 90%

Floor Space Requirements

5 - 30 %


60 - 80%


First-Pass Yields

50 - 100%


40 - 80%


75 - 125%


Customer Focus
Waste Factor: Zero customer dissatisfaction/Relationship to Profit: Customer input and feedback assures quality. Customer satisfaction supports sales.

Waste factor: Zero misalignment/Relationship to Profit: Direction and support for development improves cost, quality, and speed.

Lean Organization
Waste Factor: Zero bureaucracy/Relationship to Profit: Team-based operations reduce overhead by eliminating bureaucracy and ensuring information flow and cooperation.

Waste Factor: Zero stakeholder dissatisfaction/Relationship to Profit: Flexible relationships with suppliers, distributors, and society improve quality, cost, and speed.

Information Architecture
Waste Factor: Zero lost information/Relationship to Profit: Knowledge required for operations is accurate and timely, thus improving quality, cost, and speed.

Culture of Improvement
Waste Factor: Zero wasted creativity/Relationship to Profit: Employee participation in eliminating operations waste improves cost, quality, and speed.

Lean Production
Waste Factor: Zero non-value-added work/Relationship to Profit: Total employee involvement and aggressive waste elimination promote speedier operations and eradicate inventories.

Lean Equipment Management
Waste Factor: Zero failures, zero defects/Relationship to Profit: Longer equipment life and design improvements reduce cost. Meticulous maintenance and equipment improvements increase quality. Absolute availability and efficiency increase speed.

Lean Engineering
Waste Factor: Zero lost opportunity/Relationship to Profit: Early resolutions of design problems with customers and suppliers significantly reduces cost, while improving quality and cycle time.


Reducing inventory is an important goal of the lean organization. Carrying inventory has many costs associated with it. Obvious costs include: capital tied up in inventory and the associated loss of interest on that capita., loss due to material handling damage, increased labor costs for material handling, and increased space and storage requirement. A cost from excess inventory that is not so obvious is quality. In fact, many companies have seen quality improvements resulting from inventory reductions while not focusing on quality. The reasoning is that if an upstream process is producing parts on a machine and defects occur halfway through the batch, in an organization with low levels of inventory the next downstream process will discover the defects sooner. An organization with low inventory levels can stop the process when the defect is discovered, throw out the defective inventory, and request the previous process to start another batch. The organization with lower inventory levels will also be more effective at determining what caused the defect because the batch that the defect occurred in is fresh in the minds of both production and maintenance.


Reduced scrap and waste

Reduced inventory costs

Cross-trained employees

Reduced cycle time

Reduced obsolescence

Lower space/facility requirements

High quality & reliability

Lower overall costs

Self-directed work teams

Lead time reduction

Fast market response

Longer machine life

Improved customer communication

Lower inventories

Improved vendor support and quality

Higher labor efficiency and quality

Improved flexibility in reacting to changes

Allows more strategic management focus

Increased shipping and billing frequencies

Lean Glossary :


Andon Board: A visual control device in a production area, typically a lighted overhead display, giving the current status of the production system and alerting team members to emerging problems.

Autonomation: Automation with a human touch. Refers to semi-automatic processes where the operator and machine work together. Autonomation allows man-machine separation. Also referred to Jidoka.


Balanced production: All operations or cells produce at the same cycle time. In a balanced system, the cell cycle time is less than takt time.

Batch-and-Queue: Producing more than one piece of an item and then moving those items forward to the next operation before that are all actually needed there. Thus, items need to wait in a queue.

Benchmarking: The process of measuring products, services, and practices against those of leading companies.

Bottleneck: Any resource whose capacity is equal to, or less than the demand placed on it.

Best-in-Class: A best-known example of performance in a particular operation. One needs to define both the class and the operation to avoid using the term loosely.

Blitz: A blitz is a fast and focused process for improving some component of business ­ a product line, a machine, or a process. It utilizes a cross-functional team of employees for a quick problem-solving exercise, where they focus on designing solutions to meet some well-defined goals.


Capacity Constraint Resources: Where a series of non-bottlenecks, based on the sequence in which they perform their jobs can act as a constraint.

Catch-Ball: A series of discussion between managers and their employees during which data, ideas, and analysis are thrown like a ball. This opens productive dialogue throughout the entire company.

Cells: The layout of machines of different types performing different operations in a tight sequence, typically in a U-shape, to permit single piece flow and flexible deployment of human effort.

Chaku-Chaku: A method of conducting single-piece flow, where the operator proceeds from machine to machine, taking the part from one machine and loading it into the next.

Change Agent: The catalytic force moving firms and value streams out of the world of inward-looking batch-and-queue.

Changeover: The installation of a new type of tool in a metal working machine, a different paint in a painting system, a new plastic resin and new mold in an injection molding machine, new software in a computer, and so on.

Constraint: Anything that limits a system from achieving higher performance, or throughput.

Continuous Flow Production: Means that items are produced and moved from one processing step to the next one piece at a time. Each process makes only the one piece that the next process needs, and the transfer batch size is one. Also called "single-piece flow" or "one-piece flow."

Covariance: The impact of one variable upon others in the same group.

Current State Map: Helps visualize the current production process and identify sources of waste.

Cycle Time: The time required to complete one cycle of an operation.


Dependent Events: Events that occur only after a previous event.


Error Proofing: Designing a potential failure or cause of failure out of a product or process.


Five S: Five terms utilized to create a workplace suited for visual control and lean production. Sort means to separate needed tools, parts, and instruction from unneeded materials and to remove the latter. Simplify means to neatly arrange and identify parts and tools for ease of use. Scrub means to conduct a cleanup campaign. Standardize means to conduct Sort, Simplify, and Scrub at frequent intervals to maintain a workplace in perfect condition. Sustain means to form the habit of always following the first Ss.

Flow: A main objective of the lean production effort, and one of the important concepts that passed directly from Henry Ford to Toyota. Ford recognized that, ideally, production should flow continuously all the way from raw material to the customer and envisioned realizing that ideal through a production system that acted as one long conveyor.

Functional Layout: The practice of grouping machines or activities by type of operation performed.

Future State Map: A blueprint for lean implementation. Your organization¹s vision, which forms the basis of your implementation plan by helping to design how the process should operate.


Heijunka: A method of leveling production at the final assembly line that makes just-in-time production possible. This involves averaging both the volume and sequence of different model types on a mixed-model production line.

Hosin Planning (HP): Also known as Management by Policy or Strategy Deployment. A means by which goals are established and measures are created to ensure progress toward those goals. HP keeps activities at all levels of the company aligned with its overarching strategic plans. HP typically begins with the "visioning process" which addresses the key questions: Where do you want to be in the future? How do want to get there? When do you want to achieve your goal? And who will be involved in achieving the goals? HP then systematically explodes the whats, whos and hows throughout the entire organization.


Just-in-Time (JIT): Principles that are fundamental to Time-Based Competition ­ waste elimination, process simplification, set-up and batch-size reduction, parallel processing, and layout redesign ­ are critical skills in every facet of the lean organization. JIT is a system for producing and delivering the right items at the right time, in the right amounts. The key elements of Just-in-Time are Flow, Pull, Standard Work, and Takt Time.


Kaizen: Continuous, incremental improvement of an activity to create more value with less waste. The term Kaizen Blitz refers to a team approach to quickly tear down and rebuild a process layout to function more efficiently.

Kanban: A signaling device that gives instruction for production or conveyance of items in a pull system. Can also be used to perform kaizen by reducing the number of Kanban in circulation, which highlights line problems.


Lead Time: The total time a customer must wait to receive a product after placing an order. When a scheduling and production system is running at or below capacity, lead time and throughput time are the same. When demand exceeds the capacity of a system, there is additional waiting time before the start of scheduling and production, and lead time exceeds throughput time.

Lean: Business processes requiring less human effort, capital investment, floor space, materials, and time in all aspects of operation.


Mistake Proofing: Any change to an operation that helps the operator reduce or eliminate mistakes.

Muda: Anything that interrupts the flow of products and services through the value stream and out to the customer is designated Muda ­ or waste.


Non-Value Added: Activities or actions taken that add no real value to the product or service making such activities or action a form of waste.


Operating Expenses: The money required the system to convert inventory into throughput.

Overproduction: Producing more, sooner or faster than is required by the next process.


PDCA (Plan, Do, Check, Act)

PLAN: Senior management should use the visioning process in the context of it Business Plan. HP translates the Business Plans to action plans, meaningful to all levels of the organization.

DO: Answer the whats, hows, and whos for the total number of tiers for your organization; remember, the fewer the number of tiers, the better. Also, this is the time to bring management together and provide them with a basic understanding of HP mechanics.

CHECK: On a periodic basis, review the measurements and note what you´ve learned that can help in the future.

ACT: Make the necessary adjustments to plans and priorities in order to ensure the success of the strategy breakthroughs.

Perfection: Always optimizing value-added activities and eliminating waste.

Poka-Yoke: A mistake-proofing device or procedure to prevent a defect during order taking or manufacture. An order-taking example is a screen for order input developed from traditional ordering patterns that question orders falling outside the pattern. The suspect orders are then examined, often leading to the discovery of inputting errors or buying based on misinformation. A manufacturing example is a set of photocells in parts containers along an assembly line to prevent components from progressing to the next stage with missing parts. A poka-yoke is sometimes called a baka-yok.

Process: The flow of material in time and space. The accumulation of sub-processes or operations that transform material from raw material to finished product.

Process Kaizen: Improvements made at an individual process or in a specific area. Sometimes called "point kaizen".

Processing Time: The time a product is actually being worked on in a machine or work area.
PULL: A system of cascading production and delivery instructions from downstream to upstream activities in which the upstream supplier waits until the downstream customer signals a need. A pull system means producing only what has been consumed by downstream activities or customers.

Pull System: One of the 3 elements of JIT. In the pull systems, the downstream process takes the product they need and pulls it from the producer. This customers pull is a signal to the producer that the product is sold. The pull system links accurate information with the process to minimize waiting and overproduction.

Push System: In contrast to the pull system, product is pushed into a process, regardless of whether it is needed. The pushed product goes into inventory, and lacking a pull signal from the customer indicating that it has been bought, more of the same product could be overproduced and put in inventory.


Quality Function Deployment (QFD): A visual decision-making procedure for multi-skilled project teams which develops a common understanding of the voice of the customer and a consensus on the final engineering specifications of the product that has the commitment of the entire team. QFD integrates the perspectives of team members from different disciplines, ensures that their efforts are focused on resolving key trade-offs in a consistent manner against measurable performance targets for the product, and deploys these decisions through successive levels of detail. The use of QFD eliminates expensive backflows and rework as projects near launch.

Quick Changeover: The ability to change tooling and fixtures rapidly (usually minutes), so multiple products can be run on the same machine.

Queue Time: The time a product spends in a line awaiting the next design, order processing, or fabrication step.


Reengineering: The engine that drives Time-Based Competition. To gain speed, firms must apply the principles of reengineering to rethink and redesign every process and move it closer to the customer.

Resource Utilization: Using a resource in a way that increases throughput.


Sensei: An outside master or teacher that assists in implementing lean practices.

Sequential Changeover: Also sequential set-up. When changeover times are within Takt time, changeovers can be performed one after another in a flow line. Sequential changeover assures that the lost time for each process in the line is minimized to one Takt beat. A set-up team or expert follows the operator, so that by the time the operator has made one round of the flow line (at Takt time), it has been completely changed over to the next product.

Seven wastes: Taiichi Ohno¹s original catalog of the wastes commonly found in physical production. These are overproduction ahead of demand, waiting for the next processing stop, unnecessary transport of materials, overprocessing of parts due to poor tool and product design, inventories more than the absolute minimum, unnecessary movement by employees during the course of their work, and production of defective parts.

Single Minute Exchange of Dies (SMED): A series of techniques designed for changeovers of production machinery in less than ten minutes. Obviously, the long-term objective is always Zero Setup, in which changeovers are instantaneous and do not interfere in any way with continuous flow.

Single-Piece Flow: A situation in which products proceed, one complete product at a time, through various operations in design, order taking, and production, without interruptions, backflows, or scrap.

Standards: These involve comparison with accepted norms, such as are set by regulatory bodies.

Standard Work: A precise description of each work activity specifying cycle time, takt time, the work sequence of specific tasks, and the minimum inventory of parts on hand needed to conduct the activity.

System Kaizen: Improvement aimed at an entire value stream.

Sub-Optimization: A condition where gains made in one activity are offset by losses in another activity or activities, created by the same actions crating gains in the first activity.


Takt Time: The available production time divided by the rate of customer demand. For example, if customers demand 240 widgets per day and the factory operations 480 minutes per day, takt time is two minutes; if customers want two new products designed per month, takt time is two weeks. Takt time sets the pace of production to match the rate of customer demand and becomes the heartbeat of any lean system.

Theory of Constraints: A lean management philosophy that stresses removal of constraints to increase throughput while decreasing inventory and operating expenses.

Throughput Time: The time required for a product to proceed from concept to launch, order to delivery, or raw materials into the hands of the customer. This includes both processing and queue time.

Total Productive Maintenance (TPM): A series of methods, originally pioneered to ensure that every machine in a production process is always able to perform its required tasks so that production is never interrupted.


Value: A capability provided to a customer at the right time at an appropriate price, as defined in each case by the customer.

Value-Added Analysis: With this activity, a process improvement team strips the process down to it essential elements. The team isolates the activities that in the eyes of the customer actually add value to the product or service. The remaining non-value adding activities ("waste" are targeted for extinction.

Value Chain: Activities outside of your organization that add value to your final product, such as the value adding activities of your suppliers.

Value Stream: The specific activities required to design, order and provide a specific product, from concept to launch, order to delivery, and raw materials into the hands of the customer.

Value Stream Mapping: Highlights the sources of waste and eliminates them by implementing a future state value stream that can become reality within a short time.

Visual Control: The placement in plain view of all tools, parts, production activities, and indicators of production system performance so everyone involved can understand the status of the system at a glance.


Waste: Anything that uses resources, but does not add real value to the product or service.

Work in Progress (WIP): Product or inventory in various stages of completion throughout the plant, from raw material to completed product.


Yield: Produced product related to scheduled product.


What Are We Learning Since We Started Learning to See

What Are We Learning Since We Started Learning to See?

By Mike Rother

The Learning to See workbook, which was first made public at the Lean Enterprise Institute's June 1998 Lean Summit in Hartford, CT, has surprised us all with its ongoing success. Learning to See has now sold over 85,000 copies in English, been translated into nine languages (most recently Spanish), won the 1999 Shingo Prize for research in manufacturing, and continues to garner acclaim as a guide for lean transformations.

At first glance, Learning to See is about a method and tool for analyzing and designing value streams, but our primary intent in writing the book was to help readers widen their perspectives from a limited focus on process-level improvement to include a view of the overall flow, or "value stream.” We designed the book's format with that objective in mind, and hope that it has indeed proved to be a perspective expander for you and your team.

The flow or value stream perspective represents a shift from vertical to horizontal thinking. Horizontal thinking means looking across the traditional vertical structures of functions and departments to connect activities in the stream of value flowing from suppliers, through the organization, and on to customers. In other words, concentrating on overall flow means focusing on system efficiency rather than on just the "point efficiency" of individual elements in your organization.

Building on Toyota’s Tool
In the last few years, a flow or value stream oriented manufacturing measurable has started climbing to the top of the heap: production lead time (or it's inversely-related sibling, inventory turns). One of the main goals of most production systems today is a continual reduction of lead time, which requires that processing steps in the value stream become more closely coupled to one another, allowing value to efficiently flow across them. Toyota's original flow mapping methodology — which we expanded into Value Stream Mapping — has provided us with an especially practical tool for thinking about flow and designing value streams with shorter lead times.

With all the interest and activity around value stream mapping it seems a good time to review how the value stream perspective and the mapping tool are developing, and some lessons we have learned along the way. That is the purpose of this article. I'd like to comment on some current issues, lessons learned and reader feedback relative to value stream mapping and value stream thinking.

I. New Developments and Issues in Value Stream Mapping

• The Paper Flow is Getting More Attention
When we say lead time, we are usually thinking about production lead time, which is the time it takes to go from raw material to shipment, or from "dock to dock.” However, another type of lead time measurement is the order lead time, or the time it takes to go from a customer order to delivery.

Figure 1: Production and Order Lead Times
(Note: in make-to-order value streams, the schedule point will be further upstream than is shown here.)

When you take a close look at the flow of a customer order through many organizations, it doesn't take long to see that a significant amount of the order lead time often occurs in administrative functions; before the order even reaches the shop floor. This is another value stream, which is being called the "administrative" or "service" or "white-collar" value stream. Here too, material (i.e. orders) sits in inventory (i.e. in-baskets) and doesn't flow. As long as an administrative process is truly necessary, then we should also apply horizontal thinking and perspective here in order to design administrative value streams with short lead times.

The value stream mapping tool presented in Learning to See is increasingly being applied to administrative flows. Of course, it often takes longer to personally trace a practically invisible administrative value stream, but that's how you have to do it, because you should not rely on statements like "this is how it normally goes.” Administrative processes are also usually more make-to-order in nature, and thus different from high-volume production processes. But these obstacles should not prevent you from getting started with flow analysis and improvement across administrative processes.

In addition to the order flow, there are, of course, several other administrative and support activities in an organization, such as processing engineering changes, maintenance, quality assurance, and so on. All of these can be analyzed and redesigned with the goal of shortening their lead times. However, in such other areas, which exist primarily to support or enable the production flow, there are two additional questions that you need to be asking:
Is this activity necessary?
How should this activity be conducted in order to support the shortest possible production lead time?
In other words, never forget that the value-adding production flow is the customer that these support functions should be serving.

• Readers are Expanding Their Value Stream View into Supply Chains
Once you have initiated flow and lead-time improvement inside the four walls of your facility, you can start expanding your view to include the supply chain. More and more users of value stream mapping are reporting successes in this area, and LEI's new workbook, Seeing the Whole by Dan Jones and Jim Womack, gives you more insight and suggestions on what some are calling "macro mapping."

At one level, value stream refers to the entire flow from raw materials coming out of the earth all the way through to the hands of the end consumer; and increasingly even beyond that to include recycling the product. However, if this is too much to tackle right now then I suggest you expand your one-facility view by going from the point of use at your customer's facility back through to the receiving dock at one or two of your most important suppliers. The discoveries of waste, batched information flow and interrupted material flow that you have made inside your own facility will repeat themselves there, and issues of location and transportation between facilities will become additional factors.

Although a single-piece flow across the supply chain is usually still a dream, closer-coupling concepts like pull systems between facilities and milk-run deliveries can be applied with dramatic results. Even at the supply-chain level the basic lean goal remains the same: How can we get ever nearer to having each process make (and, if necessary, the delivery truck pick up) only what the next process needs when it needs it?

• The "Pacemaker Process" Needs More Attention
A question that often arises is, "What should we focus on as we analyze and redesign our value streams?" There are a host of factors that affect lead time (take a look at pages 30-36 in Richard Schonberger's new book, Let's Fix It), but clearly the pacemaker process — which is often a final assembly process — is one that needs more of our attention. Many manufacturers don't recognize the pacemaker process' important role in attaining a short lead time through the value stream.

Today's in-plant value streams can often be divided into two segments: pacemaker and fabrication. Definitions:
The upstream fabrication processes respond to requirements from internal customers, and often utilize general-purpose or shared equipment to produce a variety of components for different downstream processes.
In contrast, the downstream portion of a value stream is often dedicated to a particular product family and responds to external customers. This segment typically starts at the value-adding process that is the schedule and leveling point in a lean value stream (see Learning to See p.86), and involves processing steps that give the product its final form for the customer. This downstream segment of the value stream is called the pacemaker.

Figure 2: Fabrication and Pacemaker Segments of a Value Stream

The pacemaker process influences production lead time because it is the rhythm-setting point, or "heartbeat," for the value stream. If the pacemaker makes large batches of one product type, or if it has significant fluctuations in production volume, then the upstream fabrication processes will have to hold more inventory to be able to meet the peaks of the pacemaker's jerky component requirements.

In addition, due to the "bullwhip" effect (which was first described by Jay W. Forrester in 1958) any mix or volume surges at the pacemaker get amplified as you move up the value stream and into the supply chain. The effects of pacemaker fluctuations get worse the further upstream you go! (The Seeing the Whole workbook has more information on how you can assess and reduce the effects of such demand amplification in your supply chains.)

Another problem: when the pacemaker makes large batches of one product type, then your external customers who want other types have to wait, or you will have to try to hold even more finished goods inventory of items that you think customers will want. (And correctly guessing what customers will want in the future is difficult to do.)

All of this means that the efficiency of your value stream depends partly on how small you can keep the volume fluctuations and batches at the pacemaker (assembly) process. Many plants are trying to link their chain of processes by establishing supermarket pull systems between processes. However, if you run significant volume fluctuations and/or large batches in assembly, then the inventory in those supermarkets will be too high. Result: with or without pull systems the lead time through the value stream will still be long. Leveled and mixed production at the pacemaker — a steady heartbeat — helps make shorter production lead time possible.

Think of the pacemaker process as the conductor of an orchestra. To achieve lean value streams, managers, production control, maintenance, supervisors and engineers will need to pay closer attention to how you are operating your pacemakers. (Please refer to LEI's Creating Continuous Flow workbook for detailed guidelines on setting up and running operator-based pacemaker process.)

As you may have guessed, the final assembly point in a macro value stream (across several facilities and companies) is the rhythm-setting pacemaker process to which the supply chain responds. The characteristics of the information flow emanating from this point will influence a how lean a whole upstream supply chain can be.

• Leaner Value Streams Will Require Faster Response to Problems
As the lead time through a value stream shrinks, the processes in that value stream become more "close coupled" (less buffer between them). This makes a value stream more sensitive to problems. When there is a machine breakdown, absenteeism, defective parts and so on in one segment of a lean value stream it will take less time before these problems adversely affect other segments. This is especially true of problems at the pacemaker process (see above).

As it more closely couples its value streams, industry will need to work more on a heretofore largely ignored aspect of Toyota-style manufacturing: The leaner a production chain gets, the greater the need for swift, local response to abnormalities. And swift response requires swift awareness of abnormalities, someone to do the responding and a structured approach for how to respond.

A critical issue here is how management thinks about production problems. If our vision is to ban problems from production (indicated by statements like, “We just need more discipline”), then we will organize and manage differently than if we assume that problems are going to occur. There seems to be a tacit belief that Toyota’s system means the occurrence of problems will be eliminated. Yet Toyota and its suppliers also experience quality problems, machine breakdowns, absenteeism, and so on. In fact, these types of problems are statistically guaranteed to occur. And as one problem is solved and its causes eliminated, others will develop. New product programs also bring new problems.

When management assumes that problems in production are inevitable, then the most important question becomes, “How will we respond to them?” This is going to become a particularly important question for any company that is seriously trying to adopt lean production, since the faster you can successfully respond to abnormalities, the leaner you can make your value stream.

II. Notes and Advice From the Field

Learning to See has been very successful, but at the same time any book is subject to various interpretations by its readers. Here are some that we have observed as we visit and work with many companies.

• Some readers of Learning to See appear to think that value stream mapping is in itself a goal, occasionally telling us, "We are drawing maps of all our value streams!" That may lead to a better understanding of your flows, but not necessarily to any measurable improvement. Think of mapping as a method and tool to assist you in making flow improvements. The more important goal is active implementation of an improved future state.

Instead of mapping everything and expecting good things to happen as a result, we suggest you, 1) select a value stream where business objectives require measurable improvement, 2) develop an understanding of the current state, 3) design and agree upon an improved future state that can be introduced within six or 12 months, 4) put together an action plan to implement that vision (who is responsible for achieving what elements of the vision with what measurable results by when?). And in 12 months, you need to create the next future state map for that value stream and again charter a team to achieve that future state.

• We would also like to mention that having a perfectly drawn current state map is not the initial focus of VSM. A main intention of current state mapping is the process of understanding the dock-to-dock flow — the looking and sketching and trying to see and comprehend what is happening — and thinking about what should be happening — as material and information travel through your facility (or supply chain). Have you noticed that the person who best understands the material and information flows that a value stream map represents is the person who drew the map? The map creation process —more than just the map itself — helps you learn to see.

This is why we suggest that you begin sketching with just pencil and paper as you walk a flow. The looking, sketching and resketching may seem like a lot of manual work, but it is in fact a PDCA (Plan, Do, Check, Act) learning cycle that keeps you focused on the flow and deepens your understanding of the production system. With practice, you may be surprised at how quickly you can pretty accurately sketch dock-to-dock material and information flows. In other words, how quickly you can see. Then you are in a better position to develop useful future state value stream designs.

• There has occasionally been a mix-up between value stream mapping and traditional process flow charting, which is typically used by industrial engineers to analyze and improve a process. Value stream mapping (and design) cuts across process, departmental and functional boundaries, as well as across existing departmental performance-measurement systems. It involves trying to optimize dock-to dock flow instead of an individual process.

Since the value stream cuts across boundaries it means that top manufacturing management should be leading the value stream improvement effort. Although they may not necessarily do the mapping themselves, manufacturing executives and managers should be able to read a future-state value stream map and know what questions to ask.

• Some readers have focused intently on counting and tallying inventory, and using that data to estimate the production lead time as described in Learning to See. Lead time is a great metric and we recommend that you focus on reducing it. (Note: Outsourcing lead time does not equal reducing it.) However, don't let the activity of counting inventory become more important than the fundamentals of seeing and understanding the flow (or lack of flow) through your value streams.

Inventory tells you where a flow is interrupted. Once you have found these spots in your value stream then the next questions are, "Why does the flow stop here?" (there is always a reason), and, "What can we do to improve this situation?"

• Sometimes readers find it difficult to stay at the 100 ft.-level altitude the first few times they map a value stream to understand the current state. After years of making process-level improvements, you may naturally tend to drop to a very detailed level of analysis at every process along the way; trying to record all sorts of current-state process data up front. This especially seems to happen when you walk the flow through your own, familiar facility. Unfortunately, you then tend to lose the valuable overall flow perspective that Learning to See is all about.

My suggestion? Begin with the main or most important dock-to-dock branches of your value stream, and walk through them at a "100 ft. altitude.” Then go back and progressively drop down to add detail or additional branches on successive walk-throughs as is necessary to support your design and implementation of a future state. The first walk-through may only take an hour and result in only a rough current-state sketch.

The mapping process is not linear, although our presentation of it in Learning to See might lead you to believe that. You don’t really finish a current state map (“done!”), then finish a future state map (“done!”) and then shift to implementation. There is considerable overlap and feedback between these stages, and you should expect to have to periodically go back and gather more data as you realize you need it.

• We've noticed some readers going too far out into the future with their initial future state designs. Such future states are nice in theory, but about as difficult to achieve as a home run. Introducing Toyota-style production can't be done overnight, and involves steady progress via lots of base hits.

If you have drawn more than, say, six kaizen lightning bursts on a future state map, you are probably reaching too far out into the future with that map.

A suggestion is to draw one sketch of where you would like to be in about 5 years — we call this an "ideal state map" — and another, more detailed "future state map" of what you and your team can agree to have implemented within a maximum of 12 months time. Then as you work on implementing the 12-month future state you should be learning things and can fine tune your "ideal state" vision. At the end of 12 months it is time to have another 12-month map and implementation plan.

III. Reader Feedback

Our publisher, the Lean Enterprise Institute, has been open to comments and feedback from its community of readers. In addition to much positive feedback we have also received ideas and suggestions for improvements and additions to the Learning to See book, and were able to incorporate several of them in the current edition of Learning to See. There are also a handful of items that we have not added, such as:
More end-item variety to the Acme Stamping case.
Examples from different industries.
VSM in non-production settings. ("Administrative" or "white-collar" mapping.)
Detailed guidelines for managing the implementation of a future state value stream vision.
Tips for mapping across multiple facilities and organizations. ("Supply chain" or "macro" mapping.)
How to set up and run the pacemaker process.
Dealing with changing demand.
Calculating the financial benefits of a future-state design.
These — and probably more — could all be useful additions to Learning to See. But then by far the most frequent feedback of all is that the book is wonderfully straightforward, clear, and easy to understand and use. Readers are able to absorb the book and get started with positive action in their own facilities, and in many cases train others (sometimes using LEI's Training to See kit) in value stream mapping.

This makes us hesitant to complicate Learning to See with a string of detailed appendices in an attempt to make the book completely authoritative. Like any book, Learning to See reflects a need and some thinking at a point in time. The intent is to provide a springboard for seeing and thinking about your own value streams. Learning to See says what it says, does what it does, and we are pretty happy with that. You must be too, because demand for the book is still growing.

In fact, the amount of positive action, experimentation and dialog that is being triggered in part by Learning to See has been terrific. Many people are working on all manner of problems related to removing waste from their value streams. Follow-on books are being published at the Lean Enterprise Institute (such as Creating Continuous Flow, Seeing the Whole, Learning to Count), workshops are focusing on "value stream" and "value stream management," and elements of the simple (but surprisingly effective) Acme Stamping case from Learning to See keep popping up everywhere.

So Learning to See continues to serve as the fundamental value stream book, while supplements to it are being created in an even better fashion than just a couple of authors might do. Many more people are working on the issues, via several channels and with interesting perspectives.

Of course, successful implementation is what really counts. So, our hats go off to all who are rolling up their sleeves and advancing the war on waste through implementation that generates shorter lead times and positive results for customers. Keep on looking and thinking — and seeing — with a value stream perspective.

With best regards,

Mike Rother

Mike Rother is the co-author of LEI's Learning to See and Creating Continuous Flow books, as well as the Training to See training kit. He is a teacher at the University of Michigan and a manufacturing consultant based in Ann Arbor, Michigan. Mike recently returned to Ann Arbor after spending a year as guest researcher at the Fraunhofer Institute for Production Technology in Stuttgart, Germany.
Copyright © March 2002, by Mike Rother