Information Management Tools – Product and Process Design Tools, Bar Code Systems

Product and Process Design Tools

  • Computer Aided Design (CAD), Computer Aided Engineering (CAE) and Product

Data Management (PDM): CAD systems basically assist product designers in creating virtual models of products with minimal effort being consumed in the menial task of drafting. In the initial years of CAD, this was viewed as the primary advantage of computer application in design. Today, it is recognized that these models enable engineers to study product geometry and layout, and create specifications for manufacturing. More importantly, CAE software packages are available to subject these models to Finite Element Analysis (FEA), to help engineers study mechanical or thermal stresses. Most important of all, the modeling of product data in soft form lays the foundation for computer assisted manufacturing.

  • Computer Aided Process Planning (CAPP): CAPP is the link between the engineering and manufacturing processes. The objective of CAPP is the generation of detailed manufacturing instructions, given (a) the desired geometry of the end product (from the CAE/PDM database), (b) the geometry of the raw material from which it is to be used as the input in the manufacturing process, and (c) process parameters and the tools available. Two generic kinds of CAPP approaches are followed: in generative CAPP, the process plan is detailed from scratch, with the given inputs. In variant CAPP, the idea is that the process planner retrieves a similar existing process plan from a classified library of process plans and then makes the necessary minor modifications. The role of the Variant CAPP software is in retrieving a process plan closest to the one that the planner is working on. This retrieval is based on Group Technology (GT).
  • Group Technology (GT): Group Technology (GT) is a simple but immensely useful technique which, as its name suggests, deals with the grouping of items into classes based on some attribute. The classical GT problem relates to the formation of part machine families. As shown in Figure 4.3, the input to the classical part machine problem is a route sheet matrix, in which a ‘I’ in any cell indicates that the part is routed through the machine. For instance, operations on Part I are performed on machines A, C, E and G.

The objective is to form groups of parts that have common process routes. The output matrix shows that the parts can be grouped into three similar families.

Grouping can be done based on any attribute, and groups find applications in many areas process planning, as explained above is just one of them. Groups of aggregates, which have similar design attributes, can be used for speeding up the design process. GT algorithms have long been an area of interest for researchers, with algorithms ranging in complexity from those based on repeatedly sorting rows and columns after weighting them as binary numbers to those based on fuzzy ~logic and other techniques. However, the most visible impact of GT has been in the development of cellular manufacturing.

As discussed in the previous chapter, the cellular manufacturing approach pioneered at Toyota consists of arranging machines in small clusters dedicated to specific part families. The machines are usually inexpensive, general purpose machines with basic production tooling facilitating quick changeover. The clusters are typically U-shaped and they are manned by a variable number of cross-trained operators. The operator moves with the part as it is processed on each machine. Production is carried out to demand, largely based on the consumption of the part produced by the cell. If demand is low, a single operator can perform all the operations. Needless to say, capacity utilization is not a performance parameter for production personnel in this dispensation. This is how the manufacturing strategy shifts from the production-oriented capacity utilization mindset to the market-oriented demand driven mindset and is embedded in shop-floor practices.

Bar Code Systems

Bar coding is a technique for instantaneous acquisition of event data into computerized systems.

Data is stored in the form of a series of bars and white spaces, based on standards such as the Universal Product Code (UPC).

The key components of a full-fledged bar coding system are:

  • The medium-an adhesive label, card or document on which the bar code symbol is printed.
  • Printers-typically ink-jet or laser printers are used
  • Scanners-these are optical devices, mostly hand-held, consisting of an emitter, a detector and an optica1lens. They extract the bar code data from a printed bar code symbol.
  • Readers- take data reconstructed by scanners and convert into some other usable forms such as ASCII text.

Bar codes have been around for a long time now, but in India, the most visible applications are seen in postal and courier services. Globally, the spread of retailing has been a key factor pushing bar coding.

In the Indian scenario, where the major chunk of sales-in durab1es as well as in

Consumables takes place from retailers who do not have a computer, this push has been missing.

However, bar coding remains a technology with huge promise for industry applications.

For instance, consider the problem of’ as-built’ bills of material (BOMs) on project sites. These BOMs are records that track the actual usage of components on various sites or structures.

If expensive components and spares are bar coded, capturing milestone data (e.g. the date of delivery and the date of installation) become easy.

This data can then be used to monitor inventories and track warranties. Without bar coding, the same task would be immensely difficult. Similarly, bar coding can be used to maintain real-time information on order fulfillment in a job shop.

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