OPERATION MANEGEMENT

OPERATION MANAGEMENT

Operations management is an area of management concerned with overseeing, designing, and controlling the process of production and redesigning business operations in the production of goods or services. It involves the responsibility of ensuring that business operations are efficient in terms of using as few resources as needed, and effective in terms of meeting customer requirements. It is concerned with managing the process that converts inputs (in the forms of raw materials, labor, and energy) into outputs (in the form of goods and/or services). The relationship of operations management to senior management in commercial contexts can be compared to the relationship of line officers to highest-level senior officers in military science. The highest-level officers shape the strategy and revise it over time, while the line officers make tactical decisions in support of carrying out the strategy. In business as in military affairs, the boundaries between levels are not always distinct; tactical information dynamically informs strategy, and individual people often move between roles over time.

Ford Motor car assembly line: the classical example of a manufacturing production system.

Cinema queue. Operations Management studies both manufacturing and services.

According to the United States Department of Education, operations management is the field concerned with managing and directing the physical and/or technical functions of a firm or organization, particularly those relating to development, production, and manufacturing. Operations management programs typically include instruction in principles of general management, manufacturing and production systems, factory management, equipment maintenance management, production control, industrial labor relations and skilled trades supervision, strategic manufacturing policy, systems analysis, productivity analysis and cost control, and materials planning. Management, including operations management, is like engineering in that it blends art with applied science. People skills, creativity, rational analysis, and knowledge of technology are all required for success.

Production systems

In a job shop machines are grouped by technological similarities regarding transformation processes, therefore a single shop can work very different products (in these picture four colors). Also notice that in this drawing each shop contains a single machine.

Flexible Manufacturing System: in the middle there are two rails for the shuttle to move pallets between machining centers (there are also FMS which use AGVs), in front of each machining center there is a buffer and in left we have a shelf for storing pallets. Usually in the back there is a similar system for managing the set of tools required for different machining operations.

A production system comprises both the technological elements (machines and tools) and organizational behavior (division of labor and information flow). An individual production system is usually analyzed in the literature referring to a single business, therefore it's usually improper to include in a given production system the operations necessary to process goods that are obtained by purchasing or the operations carried by the customer on the sold products, the reason being simply that since businesses need to design their own production systems this then becomes the focus of analysis, modeling and decision making (also called "configuring" a production system) .

A first possible distinction in production systems (technological classification) is between process production and part production.

·         Process production means that the product undergoes physical -chemical transformations and lacks assembly operations, therefore the original raw materials can’t easily be obtained from the final product, example include: paper, cement and nylon.

·         Part production (ex: cars and ovens) comprises both manufacturing systems and assembly systems. In the first category we find job shops, manufacturing cells, flexible manufacturing systems and transfer lines, in the assembly category we have fixed position systems, assembly lines and assembly shops (both manual and/or automated operations).

Delivery lead time is the blue bar, manufacturing time is the whole bar, the green bar is the difference between the two.

Another possible classification^[13] is one based on Lead Time (manufacturing lead time vs delivery lead time): Engineer to Order (ETO, Purchase to Order (PTO), Make to Order (MTO), Assemble to Order (ATO) and Make to Stock (MTS). According to this classification different kinds of systems will have different customer order decoupling points (CODP), meaning that Work in Progress (WIP) cycle stock levels are practically nonexistent regarding operations located after the CODP (except for WIP due to queues). (See Order fulfillment)

The concept of production systems can be expanded to the service sector world keeping in mind that services have some fundamental differences in respect to material goods: intangibility, client always present during transformation processes, no stocks for "finished goods". Services can be classified according to a service process matrix:^[14] degree of labor intensity (volume) vs degree of customization (variety). With a high degree of labor intensity there are Mass Services (e.g., commercial banking bill payments and state schools) and Professional Services (e.g., personal physicians and lawyers), while with a low degree of labor intensity there are Service Factories (e.g., airlines and hotels) and Service Shops (e.g., hospitals and auto mechanics).

Metrics: efficiency and effectiveness

Operations strategy concerns policies and plans of use of the firm productive resources with the aim of supporting long term competitive strategy. Metrics in operations management can be broadly classified into efficiency metrics and effectiveness metrics. Effectiveness metrics involve:

1.   Price (actually fixed by marketing, but lower bounded by production cost): purchase price, use costs, maintenance costs, upgrade costs, disposal costs

2.   Quality: specification and compliance

3.   Time: productive lead time, information lead time, punctuality

4.   Flexibility: mix, volume, gamma

5.   Stock availability

A more recent approach, introduced by Terry Hill,^] involves distinguishing competitive variables in order winner and order qualifiers when defining operations strategy. Order winners are variables which permit differentiating the company from competitors, while order qualifiers are prerequisites for engaging in a transaction. This view can be seen as a unifying approach between operations management and marketing (see segmentation and positioning).

Productivity is a standard efficiency metric for evaluation of production systems, broadly speaking a ratio between outputs and inputs, and can assume many specific forms, for example: machine productivity, workforce productivity, raw material productivity, warehouse productivity (=inventory turnover). It is also useful to break up productivity in use U (productive percentage of total time) and yield η (ratio between produced volume and productive time) to better evaluate production systems performances. Cycle times can be modeled through manufacturing engineering if the individual operations are heavily automated, if the manual component is the prevalent one, methods used ainclude: time and motion study, predetermined motion time systems and work sampling.

ABC analysis is a method for analyzing inventory based on Pareto distribution, it posits that since revenue from items on inventory will be power law distributed then it makes sense to manage items differently based on their position on a revenue-inventory level matrix, 3 classes are constructed (A,B and C) from cumulative item revenues, so in a matrix each item will have a letter (A,B or C) assigned for revenue and inventory. This method posits that items away from the diagonal should be managed differently: items in the upper part are subject to risk of obsolescence, items in the lower part are subject to risk of stock out.

Throughput is a variable which quantifies the number of parts produced in the unit of time. Although estimating throughput for a single process maybe fairly simple, doing so for an entire production system involves an additional difficulty due to the presence of queues which can come from: machine breakdowns, processing time variability, scraps, setups, maintenance time, lack of orders, lack of materials, strikes, bad coordination between resources, mix variability, plus all these inefficiencies tend to compound depending on the nature of the production system. One important example of how system throughput is tied to system design are bottlenecks: in job shops bottlenecks are typically dynamic and dependent on scheduling while on transfer lines it makes sense to speak of "the bottleneck" since it can be univocally associated with a specific station on the line. This leads to the problem of how to define capacity measures, that is an estimation of the maximum output of a given production system, and capacity utilization.

Overall Equipment Effectiveness (OEE) is defined as the product between system availability, cycle time efficiency and quality rate. OEE is typically used as key performance indicator (KPI) in conjunction with the lean manufacturing approach.

Configuration and management

Classic EOQ model: trade-off between ordering cost (blue) and holding cost (red). Total cost (green) admits aglobal optimum.

A typical MRPII construct: general planning (top) concerned with forecasts, capacity planning and inventory levels, programming (middle) concerned with calculation of workloads, rough-cut capacity planning, MPS, capacity requirements planning, traditional MRP planning, control (bottom) concerned with scheduling.

When introducing kanbans in real production systems attaining unitary lot from the start maybe unfeasible, therefore the kanban will represent a given lot size defined by management

Value Stream Mapping, a representation of materials and information flows inside a company, mainly used in the lean manufacturing approach. The calculation of the time-line (bottom) usually involves using Little's Law to derive lead time from stock levels and cycle times

Designing the configuration of production systems involves both technological and organizational variables. Choices in production technology involve: dimensioning capacity, fractioning capacity, capacity location, outsourcing processes, process technology, automation of operations, trade-off between volume and variety (see Hayes-Wheelwright matrix). Choices in the organizational area involve: defining worker skills and responsibilities, team coordination, worker incentives and information flow.

Regarding the planning of production there is a basic distinction between the push approach and the pull approach, with the later including the singular approach of Just in Time. Pull means that the production system authorizes production based on inventory level, push means that production occurs based on demand (fore-casted or present, that is purchase orders). It should be noticed that an individual production system can be both push and pull, for example activities before the CODP may work under a pull system, while activities after the CODP may work under a push system.

Regarding the traditional pull approach a number of techniques have been developed based on the work of Ford W. Harris^[5] (1913) which came to be know as the Economic order quantity (EOQ), which formed the basis of subsequent techniques as the Wagner-Within Procedure, the News Vendor Model, Base Stock Model and the Fixed Time Period Model. These models usually involve the calculation of cycle stocks and buffer stocks, the latter usually modeled as a function of demand variability. The Economic Production Quantity^[17] (EPQ) differs from the EOQ model only in that it assumes a constant fill rate for the part being produced, instead of the instantaneous refilling of the EOQ model.

Joseph Orlickly and others developed Material Requirement Planning (MRP) at IBM, essentially a push approach to inventory control and production planning, which takes as input both the Master Production Schedule (MPS) and the Bill of Materials (BOM) and gives as output a schedule for the materials (components) needed in the production process. MRP therefore is a planning tool to manage purchase orders and production orders (also called jobs).

The MPS can be seen as a kind of aggregate planning for production coming in two fundamentally opposing varieties: plans which try to chase demand and level plans which try to keep uniform capacity utilization. Many models have been proposed to solve MPS problems:

·         Analytical models (e.g. Magee Boodman model)

·         Exact optimization algorithmic models (e.g. LP and ILP)

·         Heuristic models (e.g. Aucamp model).

MRP can be briefly described as a 3s procedure: sum (different orders), split (in lots), shift (in time according to item lead time). To avoid an "explosion" of data processing in MRP (number of BOMs required in input) planning bills (such as family bills or super bills) can be useful since they allow a rationalization of input data into common codes. MRP had some notorious problems such as infinite capacity and fixed lead times, which influenced successive modifications of the original software architecture in the form of MRP II and ERP.

In this context problems of scheduling (sequencing of production), loading (tools to use), part type selection (parts to work on) and applications of operations research have a significant role to play.

Lean Manufacturing is an approach to production which arose in Toyota between the end of World War II and the seventies. It comes mainly from the ideas of Taiichi Ohno and Toyoda Sakichi which are centered on the complementary notions of Just in Time and Autonomation (jidoka), all aimed at reducing waste (usually applied in PDCA style). Some additional elements are also fundamental:^[18] production smoothing (Heijunka), capacity buffers, setup reduction, cross-training and plant layout.

·         Heijunka: production smoothing presupposes a level strategy for the MPS and a final assembly schedule developed from the MPS by smoothing aggregate production requirements in smaller time buckets and sequencing final assembly to achieve repetitive manufacturing. If these conditions are met, expected throughput can be equaled to the inverse oftakt time. Besides volume, heijunka also means attaining mixed model production, which however may only be feasible trough set-up reduction. A standard tool for achieving this is the Heijunka box

·         Capacity buffers: ideally a JIT system would work with zero breakdowns, this however is very hard to achieve in practice, and none the less Toyota favors acquiring extra capacity over extra WIP to deal with starvation.

·         Set-up reduction: typically necessary to achieve mixed model production, a key distinction can be made between internal and external setup. Internal setups (ex: removing a die) refers to tasks when the machine is not working, while external setups can be completed while the machine is running (ex: transporting dies).

·         Cross training: important as an element of Autonomation, Toyota cross trained their employees through rotation, this served as an element of production flexibility, holistic thinking and reducing boredom.

·         Layout: U-shaped lines or cells are common in the lean approach since they allow for minimum walking, greater worker efficiency and flexible capacity.

A series of tools have been developed mainly with the objective of replicating Toyota success: a very common implementation involves small cards known as kanbans, these also come in some varieties: reorder kanbans, alarm kanbans, triangle kanbans, etc. In the classic kanban procedure with one card:

·         Parts are kept in containers with their respective kanbans

·         The downstream station moves the kanban to the upstream station and starts producing the part at the downstream station

·         The upstream operator takes the most urgent kanban from his list (compare to queue discipline from queue theory) and produces it and attach its respective kanban

The two-card kanban procedure differs a bit:

·         The downstream operator takes the production kanban from his list

·         If required parts are available he removes the move kanban and places them in another box, otherwise he chooses another production card

·         He produces the part and attach its respective production kanban

·         Periodically a mover picks up the move kanbans in upstream stations and search for the respective parts, when found he exchanges production kanbans for move kanbans and move the parts to downstream stations

Since the number of kanbans in the production system is set by managers as a constant number, the kanban procedure works as WIP controlling device, which for a given arrival rate, per Little's Law, works as lead time controlling device.

In Toyota the TPS represented more of a philosophy of production than a set of specific tools, the latter would include: SMED, Value Stream Mapping, 5S, poka-yoke, elimination of time batching, lot-size reduction, Rank Order Clustering, single point scheduling, multi-process handling and backflush accounting.

Seen more broadly JIT can include methods such as: product standardization and modularity, group technology, total productive maintenance, job enlargement, job enrichment,flat organization and vendor rating (JIT production is very sensitive to replenishment conditions).

Safety, Risk and Maintenance

Other important management problems involve maintenance policies (see also reliability engineering and maintenance philosophy), safety management systems (see also safety engineering and Risk management), facility management and supply chain integration.

  v 

OPERATION MANAGEMENT

Operations management is an area of management concerned with overseeing, designing, and controlling the process of production and redesigning business operations in the production of goods or services. It involves the responsibility of ensuring that business operations are efficient in terms of using as few resources as needed, and effective in terms of meeting customer requirements. It is concerned with managing the process that converts inputs (in the forms of raw materials, labor, and energy) into outputs (in the form of goods and/or services). The relationship of operations management to senior management in commercial contexts can be compared to the relationship of line officers to highest-level senior officers in military science. The highest-level officers shape the strategy and revise it over time, while the line officers make tactical decisions in support of carrying out the strategy. In business as in military affairs, the boundaries between levels are not always distinct; tactical information dynamically informs strategy, and individual people often move between roles over time.

Ford Motor car assembly line: the classical example of a manufacturing production system.

Cinema queue. Operations Management studies both manufacturing and services.

According to the United States Department of Education, operations management is the field concerned with managing and directing the physical and/or technical functions of a firm or organization, particularly those relating to development, production, and manufacturing. Operations management programs typically include instruction in principles of general management, manufacturing and production systems, factory management, equipment maintenance management, production control, industrial labor relations and skilled trades supervision, strategic manufacturing policy, systems analysis, productivity analysis and cost control, and materials planning. Management, including operations management, is like engineering in that it blends art with applied science. People skills, creativity, rational analysis, and knowledge of technology are all required for success.

Production systems

In a job shop machines are grouped by technological similarities regarding transformation processes, therefore a single shop can work very different products (in these picture four colors). Also notice that in this drawing each shop contains a single machine.

Flexible Manufacturing System: in the middle there are two rails for the shuttle to move pallets between machining centers (there are also FMS which use AGVs), in front of each machining center there is a buffer and in left we have a shelf for storing pallets. Usually in the back there is a similar system for managing the set of tools required for different machining operations.

A production system comprises both the technological elements (machines and tools) and organizational behavior (division of labor and information flow). An individual production system is usually analyzed in the literature referring to a single business, therefore it's usually improper to include in a given production system the operations necessary to process goods that are obtained by purchasing or the operations carried by the customer on the sold products, the reason being simply that since businesses need to design their own production systems this then becomes the focus of analysis, modeling and decision making (also called "configuring" a production system) .

A first possible distinction in production systems (technological classification) is between process production and part production.

·         Process production means that the product undergoes physical -chemical transformations and lacks assembly operations, therefore the original raw materials can’t easily be obtained from the final product, example include: paper, cement and nylon.

·         Part production (ex: cars and ovens) comprises both manufacturing systems and assembly systems. In the first category we find job shops, manufacturing cells, flexible manufacturing systems and transfer lines, in the assembly category we have fixed position systems, assembly lines and assembly shops (both manual and/or automated operations).

Delivery lead time is the blue bar, manufacturing time is the whole bar, the green bar is the difference between the two.

Another possible classification^[13] is one based on Lead Time (manufacturing lead time vs delivery lead time): Engineer to Order (ETO, Purchase to Order (PTO), Make to Order (MTO), Assemble to Order (ATO) and Make to Stock (MTS). According to this classification different kinds of systems will have different customer order decoupling points (CODP), meaning that Work in Progress (WIP) cycle stock levels are practically nonexistent regarding operations located after the CODP (except for WIP due to queues). (See Order fulfillment)

The concept of production systems can be expanded to the service sector world keeping in mind that services have some fundamental differences in respect to material goods: intangibility, client always present during transformation processes, no stocks for "finished goods". Services can be classified according to a service process matrix:^[14] degree of labor intensity (volume) vs degree of customization (variety). With a high degree of labor intensity there are Mass Services (e.g., commercial banking bill payments and state schools) and Professional Services (e.g., personal physicians and lawyers), while with a low degree of labor intensity there are Service Factories (e.g., airlines and hotels) and Service Shops (e.g., hospitals and auto mechanics).

Metrics: efficiency and effectiveness

Operations strategy concerns policies and plans of use of the firm productive resources with the aim of supporting long term competitive strategy. Metrics in operations management can be broadly classified into efficiency metrics and effectiveness metrics. Effectiveness metrics involve:

1.   Price (actually fixed by marketing, but lower bounded by production cost): purchase price, use costs, maintenance costs, upgrade costs, disposal costs

2.   Quality: specification and compliance

3.   Time: productive lead time, information lead time, punctuality

4.   Flexibility: mix, volume, gamma

5.   Stock availability

A more recent approach, introduced by Terry Hill,^] involves distinguishing competitive variables in order winner and order qualifiers when defining operations strategy. Order winners are variables which permit differentiating the company from competitors, while order qualifiers are prerequisites for engaging in a transaction. This view can be seen as a unifying approach between operations management and marketing (see segmentation and positioning).

Productivity is a standard efficiency metric for evaluation of production systems, broadly speaking a ratio between outputs and inputs, and can assume many specific forms, for example: machine productivity, workforce productivity, raw material productivity, warehouse productivity (=inventory turnover). It is also useful to break up productivity in use U (productive percentage of total time) and yield η (ratio between produced volume and productive time) to better evaluate production systems performances. Cycle times can be modeled through manufacturing engineering if the individual operations are heavily automated, if the manual component is the prevalent one, methods used ainclude: time and motion study, predetermined motion time systems and work sampling.

ABC analysis is a method for analyzing inventory based on Pareto distribution, it posits that since revenue from items on inventory will be power law distributed then it makes sense to manage items differently based on their position on a revenue-inventory level matrix, 3 classes are constructed (A,B and C) from cumulative item revenues, so in a matrix each item will have a letter (A,B or C) assigned for revenue and inventory. This method posits that items away from the diagonal should be managed differently: items in the upper part are subject to risk of obsolescence, items in the lower part are subject to risk of stock out.

Throughput is a variable which quantifies the number of parts produced in the unit of time. Although estimating throughput for a single process maybe fairly simple, doing so for an entire production system involves an additional difficulty due to the presence of queues which can come from: machine breakdowns, processing time variability, scraps, setups, maintenance time, lack of orders, lack of materials, strikes, bad coordination between resources, mix variability, plus all these inefficiencies tend to compound depending on the nature of the production system. One important example of how system throughput is tied to system design are bottlenecks: in job shops bottlenecks are typically dynamic and dependent on scheduling while on transfer lines it makes sense to speak of "the bottleneck" since it can be univocally associated with a specific station on the line. This leads to the problem of how to define capacity measures, that is an estimation of the maximum output of a given production system, and capacity utilization.

Overall Equipment Effectiveness (OEE) is defined as the product between system availability, cycle time efficiency and quality rate. OEE is typically used as key performance indicator (KPI) in conjunction with the lean manufacturing approach.

Configuration and management

Classic EOQ model: trade-off between ordering cost (blue) and holding cost (red). Total cost (green) admits aglobal optimum.

A typical MRPII construct: general planning (top) concerned with forecasts, capacity planning and inventory levels, programming (middle) concerned with calculation of workloads, rough-cut capacity planning, MPS, capacity requirements planning, traditional MRP planning, control (bottom) concerned with scheduling.

When introducing kanbans in real production systems attaining unitary lot from the start maybe unfeasible, therefore the kanban will represent a given lot size defined by management

Value Stream Mapping, a representation of materials and information flows inside a company, mainly used in the lean manufacturing approach. The calculation of the time-line (bottom) usually involves using Little's Law to derive lead time from stock levels and cycle times

Designing the configuration of production systems involves both technological and organizational variables. Choices in production technology involve: dimensioning capacity, fractioning capacity, capacity location, outsourcing processes, process technology, automation of operations, trade-off between volume and variety (see Hayes-Wheelwright matrix). Choices in the organizational area involve: defining worker skills and responsibilities, team coordination, worker incentives and information flow.

Regarding the planning of production there is a basic distinction between the push approach and the pull approach, with the later including the singular approach of Just in Time. Pull means that the production system authorizes production based on inventory level, push means that production occurs based on demand (fore-casted or present, that is purchase orders). It should be noticed that an individual production system can be both push and pull, for example activities before the CODP may work under a pull system, while activities after the CODP may work under a push system.

Regarding the traditional pull approach a number of techniques have been developed based on the work of Ford W. Harris^[5] (1913) which came to be know as the Economic order quantity (EOQ), which formed the basis of subsequent techniques as the Wagner-Within Procedure, the News Vendor Model, Base Stock Model and the Fixed Time Period Model. These models usually involve the calculation of cycle stocks and buffer stocks, the latter usually modeled as a function of demand variability. The Economic Production Quantity^[17] (EPQ) differs from the EOQ model only in that it assumes a constant fill rate for the part being produced, instead of the instantaneous refilling of the EOQ model.

Joseph Orlickly and others developed Material Requirement Planning (MRP) at IBM, essentially a push approach to inventory control and production planning, which takes as input both the Master Production Schedule (MPS) and the Bill of Materials (BOM) and gives as output a schedule for the materials (components) needed in the production process. MRP therefore is a planning tool to manage purchase orders and production orders (also called jobs).

The MPS can be seen as a kind of aggregate planning for production coming in two fundamentally opposing varieties: plans which try to chase demand and level plans which try to keep uniform capacity utilization. Many models have been proposed to solve MPS problems:

·         Analytical models (e.g. Magee Boodman model)

·         Exact optimization algorithmic models (e.g. LP and ILP)

·         Heuristic models (e.g. Aucamp model).

MRP can be briefly described as a 3s procedure: sum (different orders), split (in lots), shift (in time according to item lead time). To avoid an "explosion" of data processing in MRP (number of BOMs required in input) planning bills (such as family bills or super bills) can be useful since they allow a rationalization of input data into common codes. MRP had some notorious problems such as infinite capacity and fixed lead times, which influenced successive modifications of the original software architecture in the form of MRP II and ERP.

In this context problems of scheduling (sequencing of production), loading (tools to use), part type selection (parts to work on) and applications of operations research have a significant role to play.

Lean Manufacturing is an approach to production which arose in Toyota between the end of World War II and the seventies. It comes mainly from the ideas of Taiichi Ohno and Toyoda Sakichi which are centered on the complementary notions of Just in Time and Autonomation (jidoka), all aimed at reducing waste (usually applied in PDCA style). Some additional elements are also fundamental:^[18] production smoothing (Heijunka), capacity buffers, setup reduction, cross-training and plant layout.

·         Heijunka: production smoothing presupposes a level strategy for the MPS and a final assembly schedule developed from the MPS by smoothing aggregate production requirements in smaller time buckets and sequencing final assembly to achieve repetitive manufacturing. If these conditions are met, expected throughput can be equaled to the inverse oftakt time. Besides volume, heijunka also means attaining mixed model production, which however may only be feasible trough set-up reduction. A standard tool for achieving this is the Heijunka box

·         Capacity buffers: ideally a JIT system would work with zero breakdowns, this however is very hard to achieve in practice, and none the less Toyota favors acquiring extra capacity over extra WIP to deal with starvation.

·         Set-up reduction: typically necessary to achieve mixed model production, a key distinction can be made between internal and external setup. Internal setups (ex: removing a die) refers to tasks when the machine is not working, while external setups can be completed while the machine is running (ex: transporting dies).

·         Cross training: important as an element of Autonomation, Toyota cross trained their employees through rotation, this served as an element of production flexibility, holistic thinking and reducing boredom.

·         Layout: U-shaped lines or cells are common in the lean approach since they allow for minimum walking, greater worker efficiency and flexible capacity.

A series of tools have been developed mainly with the objective of replicating Toyota success: a very common implementation involves small cards known as kanbans, these also come in some varieties: reorder kanbans, alarm kanbans, triangle kanbans, etc. In the classic kanban procedure with one card:

·         Parts are kept in containers with their respective kanbans

·         The downstream station moves the kanban to the upstream station and starts producing the part at the downstream station

·         The upstream operator takes the most urgent kanban from his list (compare to queue discipline from queue theory) and produces it and attach its respective kanban

The two-card kanban procedure differs a bit:

·         The downstream operator takes the production kanban from his list

·         If required parts are available he removes the move kanban and places them in another box, otherwise he chooses another production card

·         He produces the part and attach its respective production kanban

·         Periodically a mover picks up the move kanbans in upstream stations and search for the respective parts, when found he exchanges production kanbans for move kanbans and move the parts to downstream stations

Since the number of kanbans in the production system is set by managers as a constant number, the kanban procedure works as WIP controlling device, which for a given arrival rate, per Little's Law, works as lead time controlling device.

In Toyota the TPS represented more of a philosophy of production than a set of specific tools, the latter would include: SMED, Value Stream Mapping, 5S, poka-yoke, elimination of time batching, lot-size reduction, Rank Order Clustering, single point scheduling, multi-process handling and backflush accounting.

Seen more broadly JIT can include methods such as: product standardization and modularity, group technology, total productive maintenance, job enlargement, job enrichment,flat organization and vendor rating (JIT production is very sensitive to replenishment conditions).

Safety, Risk and Maintenance

Other important management problems involve maintenance policies (see also reliability engineering and maintenance philosophy), safety management systems (see also safety engineering and Risk management), facility management and supply chain integration.

  vv