Useful Notes on Models for Production and Operations Systems

The objective of any production/operations system is to add value to outputs (goods or services) following a framework of activities. A sample of production/operations system can be expressed mathematically as under:

Y= f (c₁ c₂, c₃……… c_n)

Where ‘Y is the output and c_1, c₂, c₃, ………… c_n are the inputs.

What should be the type of production/operations systems would again depend on number of factors. Broadly, however, it depends on nature of products/services and type of production. While nature of products/services may be anything like, chemical, pharmaceutical, textile, electronic, banking, telecommunication, BPO/HRO, etc the type of production/operations may be engineering, process, extraction, cognitive, etc.

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To determine the outcomes of proposed courses of action in POM, we use different models. A model is defined as a replica or abstraction of important characteristics of a process. It explains the interrelationships between various factors of a POM process. By simulating models, we can understand the problems, if any, in a given POM system. In POM, we generally use the following type of models—

Verbal/Written/Descriptive/Physical Models:

All these models are categorized under one group because of their commonality to explain the situation by scaling down to a manageable limit. Verbal/written/descriptive models explain a situation in words, while physical models explain a situation by a physical replica duly scaling down a machine or a structure. Physical models are also known as iconic models.

Schematic Models:

These are shown by charts, graphics, maps of routings, network diagrams, etc.

Mathematical Models:

These show functional relationships among different variables using mathematical symbols and equations. In POM, we use two types of mathematical models:

i. Optimization models, which help to analyse problems and suggest solution

ii. Heuristics models, which are some established decision-making procedures to solve a problem

In linear programming, we by to achieve best feasible solution within some given constraints. This is one example of optimization model, which we use in POM. Another example of optimization model can be a simple equation as under:

TC = F+ vN

Here, we assume total cost (TC) is the function of fixed (F) and variable unit cost (vN).

Heuristic model is a rule of thumb (e.g., set of steps) that we use in POM for a solution to a problem, which may not, however, be optimal. For line balancing, i.e., the assessment of total work to be done or performed on a line, duly breaking the tasks and assigning the tasks to work stations, we use heuristic models. Here, we apply a set of rules systematically as an algorithm.

Using various models, we can control the variables in production/operations systems, understand the cost implications and make best trade-offs among costs. Throughout the book, we have used various models for explaining the POM systems.