Production planning, scheduling and control process

The approaches that with respect to the planning, scheduling and production control process have been treated by various authors such as Schroeder, Tawfik & Chauvel, Nahmias, Rigss, Buffa & Sarin, Meredith & Gibbs among others, who establish In general terms, this begins with the forecasts, from which the long, medium and short term plans are derived.

This approach, in the opinion of the author, has some shortcomings, since it lacks the integrating concept that in the vertical sense, must start in the business strategy and that in the horizontal sense, it must be related to the other subsystems of the organization.

Other authors such as Starr,, Companys Pascual,, Ploss, and Chase & Aquilano, Adam & Ebert, offer production management models in their works that, despite establishing an integrating concept in the vertical sense, do not clearly express integration in the horizontal direction. Perhaps they are Vollmann et al and Domínguez Machuca et al, who, according to the literature consulted, present a better approach, since they consider integration in both directions.

In this regard, this last author affirms that the production planning and control process must follow a hierarchical approach, in which a vertical integration between the strategic, tactical and operational objectives is achieved and also its horizontal relationship with the others is established. functional areas of the company.

Basically the five phases that make up the production planning and control process are:

1. Strategic or long-term planning Aggregate or medium-term planning Master programming Component programming Execution and control

It is important to note that according to Domínguez Machuca, these phases should be carried out in any manufacturing company, regardless of its size and activity, although the way in which they are developed will depend on the characteristics of each production system. Figure 1 summarizes the main phases mentioned together with the plans derived from them, relating, on the one hand, the levels of business planning and, on the other, planning and capacity management.

Taking into account the aspects that must be considered in the process of planning, scheduling and control of production and for the sake of its importance in the actions to improve the competitive capacity of an organization, the following will proceed to analyze in detail the contributions from different authors regarding concepts, methods and techniques most used in each of its phases.

Planning, programming and production control process Source: Domínguez Machuca José Antonio, 1995.

1. Forecasts

In approximation to what was expressed by Rigss, Domínguez Machuca et al, Buffa & Sarin, Adam & Ebert, Hanke & Deitsch and Voris, it can be stated that forecasts are the first step in the production planning process and these serve as starting point, not only for the development of strategic plans, but also for the design of medium and short-term plans, which allows organizations to roughly visualize future events and largely eliminate uncertainty and react quickly to changing conditions with some degree of precision.

From the conceptual point of view, some authors express the importance of differentiating between the terms prediction and forecast, since according to their criteria, predictions are based merely on the consideration of subjective aspects within the process of estimating future events, while that forecasts are developed through scientific procedures, based on historical data, which are processed using quantitative methods.

Regarding the types of forecasts, these can be classified according to three criteria: according to the time horizon, according to the economic environment covered and according to the procedure used.

Forecasts according to the time horizon can be long-term, medium-term or short-term and their use ranges from the preparation of plans at the strategic level to those at the operational level.

Forecasts according to the economic environment can be of a micro or macro type and are defined according to the degree to which small details are involved vs. great values ​​summed up.

The forecasts according to the procedure used can be of a purely qualitative type, in those cases in which an open manipulation of data is not required and only the judgment or intuition of the forecaster is used, or purely quantitative, when mathematical and statistical procedures are used. They do not require the elements of judgment.

Perhaps this last classification is the most generalized by the different authors consulted according to which, the qualitative and quantitative methods that can be applied in the elaboration of the forecasts are the following:

• Qualitative Methods: Delphi Method, Informed Judgment Method, Life Cycle Analogy Method, and Market Research Method Quantitative Methods: Time Series Methods and Causal Methods.

A classification of the methods applied in forecasting, based on Hanke & Deitsch and Schroeder, is presented in Table 1.

Table 1. Classification of forecasting methods

Based on: Hanke & Deitsch and Schroeder.

QUALITATIVE METHODS	Name	Prediction horizon
Delphi	Medium and long term
Informed judgment	Short term
Life cycle analogy	Medium and long term
Market research	Short and medium term

METHODS QUANTITATIVE	Type	Name	Horizon
SERIES OF WEATHER	Not formal	Short
Simple average	Short
Moving average	Short
Exponential smoothing	Short
Linear exponential smoothing	Short
Quadratic exponential smoothing	Short
Seasonal exponential smoothing	Short
Adaptive filtering	Short
Classical decomposition	Short
Exponential trend models	Medium and long
S curve fit	Medium and long
Gompertz model	Medium and long
Growth curves	Medium and long
Census II	Short
Box-Jenkins	Short
CAUSALS	Simple regression	Medium
Multiple Regression	Medium
Main indicators	Short
Econometric models	Short
Multiple regression of time series.	Medium and long

It is evident that one of the main problems of the operations manager is to select the best forecasting method, which must obey, in the case of quantitative methods, the historical behavior of the data, based on the analysis of patterns. of average behavior, trend, seasonal cycles and random elements. In the event that historical data does not exist or is unreliable, it is best to use a qualitative method, which, although they do not offer a high degree of security, are better than nothing.

One of the elements of judgment that allow the selection of the method is provided by the error analysis, which expresses the difference between the real and predicted data. The most common forecasting error calculation methods are: Average Error, Mean Absolute Deviation (MAD), Mean Square Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Deviations per Period (BIAS).

In any case, the best forecast is one that, in addition to manipulating historical data through a quantitative technique, also makes use of judgment and common sense using the knowledge of experts.

1. Long-term planning

One of the expressed needs, on the way to improve competitiveness, is the adoption of a correct operations strategy, which is defined by Schroeder as a vision of the operations function that depends on the general direction or impulse for the taking of decisions. This vision must be integrated with the business strategy and is often, but not always, reflected in a formal plan.

The operations strategy must result in a consistent pattern of decision making in operations and a competitive advantage for the company. Likewise, Chase & Aquilano express, as an important aspect to consider, that said strategy must specify the way in which the company will use its productive capacities to support the corporate strategy. All this means that the operations strategy must arise from a long-term business strategy and, in turn, must be integrated horizontally with the strategies of the other subsystems of the company.

According to this statement and in accordance with Domínguez Machuca et al, the operations strategy is constituted as a long-term plan for the operations subsystem, in which the objectives to be achieved and the courses of action are collected, as well as the allocation of resources to different products and functions. All this must pursue the achievement of the global objectives of the company within the framework of its corporate strategy, also constituting a consistent pattern for the development of the tactical and operational decisions of the subsystem. This does not differ from the concept of Schroeder, who also adds that the operations strategy must be a functional strategy that must be guided by the business strategy and whose heart must be constituted by the mission, distinctive competence, objectives and policies.

In line with the above, Domínguez Machuca et al state that the two basic functions that the operations strategy must fulfill are:

1. Serve as a frame of reference for the planning and control of production, from which it is its starting point. Set the guidelines that allow to appreciate to what extent the operations subsystem is collaborating in the achievement of the corporate strategy.

Within this purpose, the basic decisions that must be considered within the operations strategy are:

1. Positioning decisions, which affect the future direction of the company and within which are included the long-term objectives, the establishment of competitive priorities, the setting of the quality management model, the selection of products and the selection of Processes Design decisions, concerning the operations subsystem, which imply long-term commitment and among which are the design of products and processes, workforce, the appropriation of new technologies, capacity decisions, location and distribution of supply systems and facilities.

1. Aggregate Planning

Aggregate planning, also called combined planning, is located at the tactical level of the hierarchical planning process and its fundamental mission, in approximation to the approach of several authors, is to establish production levels in aggregate units throughout a horizon. of time that generally fluctuates between 3 and 18 months, in such a way that the needs established in the long-term plan are met, while maintaining minimum levels of costs and a good level of customer service.

The term aggregate, at this level of planning, implies that the quantities to be produced must be established globally or as expressed by Schroeder for a general measure of production or at most for a few categories of accumulated products. According to Nahmias, it may be advisable to use aggregate units such as product families, unit of weight, unit of volume, time of use of labor power or value in money. In any case, any aggregate units chosen must be meaningful, easily manageable, and understandable within the plan.

On the other hand, within the process of preparing the aggregate plan and in order to fulfill its fundamental objective, it is important to manage the variables that may influence it, which can be classified into two large groups: First, they are supply variables, which allow modifying production capacity through overtime programming, hiring temporary workers, subcontracting units and cooperation agreements; secondly, there are the demand variables, which can influence market behavior through advertising, price management, promotions, etc.

Likewise, there are several strategies for the elaboration of the aggregate plan, which have been classified by most of the authors into two groups, subdivided as follows::

1. Pure strategies:

• Level labor force (with employment of overtime or temporary workers) Strategy of pursuit, adaptation to demand or hunting: (with or without employment of subcontracting).

1. Mixed strategies: They are carried out by mixing several pure strategies.

Due to the different strategies that can be adopted, a plan must be obtained that satisfies the internal constraints of the organization while keeping the cost of using resources as low as possible.

Regarding the existing techniques in the elaboration of aggregate plans, according to the consulted authors (Ibídem), the most renowned are the following:

1. Manual methods of graphs and tables Mathematical and simulation methods: linear programming (simplex method and transport method), quadratic programming, simulation with search rules (Search Decision Rules) and programming with simulation Heuristic methods: method of management coefficients, PSH method (Production Switching Heuristic), linear decision rules (LDR) and search for decision rules (SDR).

A comparative analysis about some of the aforementioned techniques was developed by Chase & Aquilano and is presented in Table 2.

Table 2. Comparison between some aggregate planning methods.

Source: Chase & Aquilano, 1995, p. 632.

METHODS	HYPOTHESIS	TECHNIQUE
Charts and Tables	None	Alternative testing of plans by trial and error. It is not optimal but it is easy to develop and understand.
Programming with simulation	Existence of a computer-based production program.	Try aggregate plans developed by other methods.
Linear programming, transport method	Linearity, constant workforce.	Useful for the special case where hiring and firing costs are not a factor. Provides an optimal solution.
Linear programming, simplex method	Linearity	It can handle any number of variables, but it is often difficult to formulate. Provides an optimal solution.
Linear decision rules.	Quadratic cost functions	It uses mathematically derived coefficients to specify production rates and workforce levels in a series of equations.
Management coefficients	Managers basically make good decisions	Use statistical analysis of previous decisions to make new decisions. It applies to a single group of managers and is not optimal.
Decision search rules	Any type of cost structure	Use pattern-finding procedures to find minimum costs from total cost curves. Difficult to develop, it is not optimal.

It should be noted that, due to their easy understanding, perhaps the most widely used by businessmen are the manual type through graphs and tables.

1. Master program

Once the aggregate plan is completed, the next step is to translate it into specific final units or items. This process is what is known as disaggregation, subdivision or decomposition of the aggregate plan and its final result is called the Master Production Schedule (MPS).

Basically, it can be said that a master production schedule is a detailed plan that establishes the specific quantity and exact dates of manufacture of the final products. In this regard, Vollmann et al add that an effective MPS should provide the basis for establishing customer shipping commitments, effectively utilizing plant capacity, achieving company strategic goals, and resolving manufacturing-marketing negotiations.

The units in which an MPS can be expressed are:

• Finished items in a continuous environment (Make to stock) Modules in a repetitive environment (Assemble to stock) Customer order in a workshop environment (Make to order).

Regarding the time horizon of an MPS, most of the authors agree that this can be variable and that depending on the type of product, the production volume and the delivery time components, this can range from one hour to several weeks and months, with reviews, generally weekly. Likewise, Chase & Aquilano, add that, in order to maintain control and avoid chaos in the development of the MPS, it is important to subdivide its time horizon into three frames:

• Fixed: Period during which it is not possible to make modifications to the PMP. Fixed medium: The one in which changes can be made to certain products. Flexible: A further period of time, in which it is possible to make any modification to the MPS.

Regarding the inputs for obtaining the MPS, it is important to consider the following elements: the aggregate plan in product units, the short-term sales forecasts in product units, the firm orders committed to the customers, the available capacity of the facility or work center and finally, other sources of demand.

Within the MPS formalization process, some of the key functions that it must fulfill are:

• Translate aggregated plans into specific end items Evaluate scheduling alternatives Generate material requirements Generate capacity requirements and maximize utilization Facilitate information processing Maintain valid priorities

With regard to the existing techniques to disaggregate the aggregate plan and translate it into a MPS, some analytical and simulation models have been developed which, in the opinion of the cited authors, suffer from the same problems of aggregate planning, being the most important use by entrepreneurs, trial and error methods. However, Narasimhan et al, suggest the existence of other methods for disaggregation, namely:

• Cut-and-fit method: Tests various capacity distributions for products in a group until a satisfactory combination is determined Mathematical programming methods: Optimization models that allow for cost minimization Heuristic methods: Like In aggregate planning, they allow reaching satisfactory but not optimal solutions.

Finally and according to Vollmann, it is important to note that a good MPS must take into account capacity limitations and remain feasible from this point of view, which can be achieved by applying the following techniques:

• Capacity Planning Using Overall Factors (CPOF) Capacity Bills (Capacity Bills) Resource profiles (Resourse profiles)

Of these, the most used are the last two due to their greater accuracy.

Regarding component programming, which corresponds to the next stage of the hierarchical approach, it has been preferred to give it a differentiated treatment and therefore it will be published in a later document.

1. Execution and control of production

The last step in the hierarchical planning and control process is the final operations program, which will allow each worker or person in charge of a work center to know what to do to comply with the materials plan and with it, the MPS, the aggregate plan and the strategic plans of the company.

These activities are framed within the execution and control phase, which in the case of manufacturing companies is called workshop management. A job shop, according to Chase & Aquilano, is defined as a functional organization whose departments or work centers are organized around certain types of equipment or operations; In them, products flow through the departments in batches that correspond to customer orders.

It is important within this management phase, to take into consideration the type of production configuration that the workshop has, because depending on this, it will also be the technique or procedure to be used in its programming and control. Basically, the generality of the consulted authors, suggests that the configuration of the workshops can be of two types:

1. Continuous or serial configuration workshops: Those where machines and work centers are organized according to the manufacturing sequence (assembly lines), with stable and specialized processes in one or a few products and in large batches. In them, scheduling activities are mainly aimed at adjusting the production rate periodically.Batch configuration workshops: In which the distribution of machines and work centers are organized by functions or departments with sufficient flexibility to process diversity of products. These can be of two types:

• Configured in Flow Shop: Where the different products follow the same manufacturing sequence. Configured in Job Shop: Those where the products follow different manufacturing sequences.

Likewise, in practice, many workshops, due to the manufacturing needs and competitive demands of the current market, have adopted hybrid configurations, of which the most generalized is the cellular configuration or manufacturing cells. These constitute a manufacturing system designed to process families of parts, with a physical distribution such that it allows to simplify planning and control procedures.

In general terms and in the most complex case, the activities that are presented in programming and control Operations are: Load Assignment, Order Sequencing and Detailed Scheduling. To these, Adam & Eber t, add two others: Fluidity and Input / output control (input / output control).

The fulfillment of these activities should answer the following questions from the programmer:

1. What capacity is needed in the workplace? What delivery date should be promised on each order? When to start each order? How to ensure that orders are finished on time?

Question 1 can be solved through load analysis; Questions 2 and 3 are solved with the application of Sequencing techniques and detailed programming, and question 4 with the fluidity analysis and input-product control.

Asignación de carga: En aproximación a los conceptos de Heizer & Render, Adam & Ebert, Lockyer, Schroeder y Domínguez Machuca et al, esta se define como la asignación de tareas a cada centro de trabajo o de proceso, que permite controlar la capacidad y la asignación de actividades específicas en cada centro de trabajo. En general las técnicas más empleadas en la asignación de carga son: Gráficos Gantt, perfiles de carga o diagramas de carga, métodos optimizadores (algoritmo de Kuhn o método Húngaro) y soluciones heurísticas (método de los índices).

Order sequencing: This activity consists of determining the order in which orders will be processed in each work center, once the existence of capacity has been established.. The Sequencing problem becomes more complex as the number of work centers increases, regardless of the number of orders; Likewise, it is important to take into account the type of configuration of the workshop, since the applicability of the different techniques depends on this. With regard to workshops configured in Flow Shop, the best known techniques are:

1. Sequencing techniques on one machine: Hungarian algorithm, Kauffman algorithm, SPT rule, and the goal pursuit method used in Kanban systems Sequencing techniques on several machines: Johnson's rule for N orders and two machines, Johnson's rule for N orders and three machines and rules for N orders and M machines (Campbell-Dudek-Schmith algorithm, Bera algorithm, simulation techniques, expert systems and more recently the Assisted Cooperative Systems).

For the workshops configured in Job Shop, due to the diversity in the sequence of operations, it is not possible to use any optimization technique, therefore, the sequence of operations is established according to the specific objectives of each programmer, through the use of priority rules.

A compilation made in the works of several authors, allows to determine that the most used priority rules are:

• FCFS: First come / First serve. FISFS: First In System / First Serve (first in system, first served) SPT: Shortes Processing Time.EDD: Earliest Due date.CR: Critical Ratio (critical ratio).LWR: Least Work Remaining (minimum work remaining).FOR. Fewest Operations Remaining (minimum number of remaining operations).ST: Slack Time (slack time).ST / O: Slack Time per Operation (slack time per operation).NQ: Next Queue (next in queue).

Detailed scheduling: Determines the start and end times of the activities of each work center, as well as the operations of each order for the sequence performed.. The most commonly used techniques are: forward and backward scheduling, shipping lists, Gantt charts, and finite capacity scheduling.

Fluidity: It allows to verify that the planned times are met, so that, if there are deviations in the real production, corrective measures can be taken in time..

Input / Output Control: They control the levels of capacity utilization of each work center, through input / output reports.

To conclude and in line with Domínguez Machuca et al and Dilworth, it is important to clarify that regardless of the chosen technique, the detailed programming and control of short-term operations must be designed and executed based on the achievement of two basic objectives: reducing costs and increasing customer service.

1. Conclusions

From the different authors consulted, it is concluded that the hierarchical approach to planning, programming and control of production, presents the most complete perspective in the development of the tasks that encompass this function, since it allows a complete integration in the vertical sense starting from long-term decisions at the tactical levels down to the more detailed aspects of programming in the very short term; Likewise, it allows integration in the horizontal sense in such a way that the production function interacts dynamically with the other functions of the company. Within the planning, programming and control process that this approach raises, the phases that are applicable to any type of company and through which the operations manager must go are:Long-term or strategic planning. Medium-term or aggregate planning. Master programming. Component programming and Execution and control. The development of these phases will depend on the type of company and the complexity of its operations and only through them will the organization approach better levels of competitiveness and productivity.

1. Bibliography

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