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Chapter 3 - Shop Floor Control

3.1 What is shop floor control (SFC)?

3.1.1 - Definition

Shop Floor Control is defined as a system for utilizing data from the shop floor to maintain and communicate status information on shop/manufacturing orders and work centers.  (Higgins, Leroy and Tierney 1996). It forms the foundation of a production planning and control system and therefore plays a crucial role in the overall design of a manufacturing system. However since manufacturing systems are of such a large variety, different SFC designs exist and these are typically customizations that fit the specific needs of a given shop floor.

 

Scherer  points out that the topic of Shop Floor Control is not well understood owing to a theory and practice gap between the situation in industry and in academia. In industry operator experience, motivation and qualifications form the basis of Shop Floor Control while academia concentrates on the problem of scheduling and its solution.  In describing the situation in industry, he identifies the shop floor as a provider of physical goods He further states that it is faced with the challenge of becoming an agile entity within an enterprise and within a network of enterprises forming a virtual organization. He states that this challenge is posed by the current production environment, which is constantly faced by changes and dominating customer demand. An example of a study that tries to reconcile this gap is by Kenneth Mackay and John Buzacott whose paper entitled “The application of computerized production control systems in job shop environments” analyzes how the computer helps the scheduler to do the task of scheduling in a job shop environment. In his paper, he points out that analytical and alogorithmic aids have limited benefits to a typical job shop. He suggests that the appropriate use of computer technology can address information overload, cue filtering and assist the scheduler in problem solving.

 

 3.1.2 Objectives of Shop Floor Control

Spearman and Hopp point out that Shop Floor Control plays an integral role in production and when properly implemented it satisfies 4 objectives:

i.                     It creates the ideal production system. In the various literature surveyed, the ideal case was described as a pull system (to be defined later in the chapter).

ii.                   It provides an enabling environment for the workers that makes the entire production system easy to understand. As a result the system becomes easy to use.

iii.                  It integrates easily with other planning functions. In the case of MRP II, this would mean an ability to execute the plans generated in long range planning and intermediate planning as well as providing feedback to refine these functions.

iv.                 It is has the flexibility to accommodate new ideas and changes. This objective is aimed at creating an agile system that can meet the challenges currently faced in industry. (Spearman and Hopp 1996,424)

 

 

3.1.3 Functions in  Shop floor Control

Spearman and Hopp identify four general functions that are carried out in Shop Floor Control

-         It co-ordinates the manufacturing resources (material, knowledge, humans and information) on the shop floor. Material flow control, which is a fundamental activity in most systems, falls under this category. This function provides a mechanism that decides which job to release to the factory, which job to work on at the individual workstations and what material to move between workstations.

 

-         It provides real time control. Real time simulations can be created based on the behavior of a plant which is determined by analyzing three sets of data:

-         Standard WIP which refers to the quantity and location of material between different manufacturing processes.

-         Status monitoring which involves the surveillance of manufacturing resources other than material such as staffing levels and machine status.

-         Throughput tracking which involves measuring the output from a line or plant against an established production quota or customer due date. This can then be used to forecast the need for overtime or staffing shifts.

 

-         It carries out capacity feedback, which involves the collection of data to update capacity estimates so as to ensure consistency between high level planning modules and low level execution ones.

 

-         It enables quality control by giving the operator of a downstream workstation the authority to refuse parts from an upstream workstation on the basis of inadequate quality. (Spearman and Hopp 1996, 425)

 

1.2  What are the characteristics of a good SFC design?

Scherer describes shop floor control from a systems perspective. He notes that in order to achieve control within the shop floor, the designer’s goal should be that of developing a dynamic and flexible organization as opposed to finding an optimal design. He gives a further breakdown of the SFC system using two different perspectives:

-         Using cybernetic systems theory, the shop floor is part of a larger cybernetic system that is highly complex and has chaotic behavior. In such a system, the behavior is predictable only for a short time because of the interactions, feedback and coupling between the different aspects of the manufacturing system. The dynamics of behavior of the formal logic system and its state variables as encountered in the real world can subsequently be used to describe shop floor control.

 

-         Using sociotechnical systems theory, emphasis is laid on the role of humans in production as they interact with machines on the shop floor. By using the patterns of social and human behavior, it is possible to describe and understand the action and logic of organizational development of informal systems.  (Scherer 1998, 453).

 

With these two definitions in mind, Scherer proposes that the two important parameters to consider in designing a control system (hence the SFC module) are the structure of the system and the individual work tasks.

In terms of structure, Spearman identifies three important considerations to bear in mind when designing the SFC.

1.      Gross capacity control – Gross Capacity Control ensures that the lines on the plant floor are close to optimally loaded when running. This creates a stable environment for the production system. Gross capacity control can be achieved by varying shifts, staffing levels, days per week and hours per day or by using outside vendors.

2.      Bottleneck planning – Bottle neck refers to the slowest process in a production system. Stable bottle neck provide the most ideal situation because they are easier to maintain than moving ones. It is worth noting however that bottlenecks can be designed by adding capacity to some stations so that throughput is never constrained.

3.      Span of control – Span of control refers to the number of employees under the direct supervision of a manager as well as range of products and/or processes to be supervised. An ideal system will provide the manager with information about what is needed further downstream as well as information about the materials that will be arriving at different stations. This information enables him to plan effectively.

 

According to Scherer, a design that takes into account the individual work tasks should be able to instill a capacity for self-design and lasting adaptability in the shop floor control module. A system with this capacity gives the human an opportunity to achieve three things:

-         Learn based on his qualifications and motivation

-         Gain experience through errors

-         Apply knowledge by carrying out independent actions.

In this way the human can contribute to the increased flexibility and adaptability of the entire production system without being driven to do so by people higher in the hierarchical framework.  Ultimately, this enables the SFC module to meet objectives (i) and (iv) described above. 

 

3.3 SFC in Push systems and Pull systems

In general, SFC systems are classified into two categories, Push and Pull, based on four different criteria. These are described below under separate headings. Benton and Shin provide the first three classifications while the fourth is proposed by Professor Cochran of the MIT Production System Design laboratory.

 

1.      Nature of the order release (De Toni et al, 1988; Karmakar, 1989; Ding and Yuen 1991) -In pull systems, the order release by which the flow of materials or components is initiated gets triggered by the removal of an end item or a fixed lot of end items. In push systems, production or material flow is initiated in anticipation of future demand.

 

2.      The structure of information flow (Olhager and Ostlund 1990; Hodgson & Wang (1991 a,b)) – In pull systems, local demand from the next server triggers the physical flow of materials. The local demand refers to orders while the server refers to a workstation. Such a system is a decentralized control strategy where the ultimate goal of meeting orders is disregarded in local workstations. Push systems use global and centralized information in the form of customer orders and demand forecasts which are released and processed to control all the levels of the production cycle.

 

3.      Practical approach associated with WIP level on the shop floor (Spearman and Zazanis 1992) – In pull systems, a closed queuing network is characterized by a bounded Work In Process (WIP). This places a cap on the maximum amount of WIP that can be found within a cell or between workstations on the shop floor. Push systems are characterized by an open queuing network with infinite queuing space.

 

4.      Type of control system based on the classical control model (David S. Cochran 1994) – A pull system provides feedback each time a unit is produced. It uses a decoupler to detect the difference between the desired quantity and the actual quantity produced. The resulting error is converted into a signal that initiates production of the machines upstream of the decoupler. A push system is an open loop control system whereby the feedback in the output quantity is not used to effectively control the manufacturing system. Any disturbance occurring to the system causes a change in the output which is however not detected until the following planning cycle. This change is caused by the time delay in information.

 

Uday Karmakar summarizes the advantages of the two systems as follows:

Pull systems -  are cheaper because they don’t need computerization (software and hardware); leave control and responsibility at the local level; and offer attractive incentives for lead time management.

 

Push systems –  are good at material planning and co-ordination; provide a hub for inter-functional communication and data management  due to their centralized control;  and are good at computing quantities for work releases by interpreting forecasts into discrete product orders but not so much for timing .The inability to meet the timing is caused by the lack of dependable feedback based on the output of the system.

 

By combining these complementary set of strengths, hybrid systems end up solving the weaknesses found in MRP II. Based on the above classifications and advantages, MRP II can be classified as a push system.