Design for service, with particular emphasis on machines working in dirty environments

Citation

Ranky, P.G. (1998), "Design for service, with particular emphasis on machines working in dirty environments", Industrial Robot, Vol. 25 No. 3. https://doi.org/10.1108/ir.1998.04925caa.002

Design for service, with particular emphasis on machines working in dirty environments

Design for service, with particular emphasis on machines working in dirty environments

The author

Paul G. Ranky is a professor at the Department of Industrial and Manufacturing Systems Engineering, New Jersey Institute of Technology (NJIT), Newark, NJ 07102, USA. E-mail: ranky@admin.njit.edu. He is also the Guest Academic Editor of this issue.

Design for manufacturing, assembly, quality and service is evident in the case of machines and products that have been designed for being capable of functioning in harsh, dirty environments. As one example, consider the General Motors cargo and/or troop carrier, the "Hummer", or as often called, the "Humwee", a popular army truck (see plates 1 and 2) as well as "family fun car", in its converted form, both in the USA and Europe.

The Hummer is a good example of designing for service with all of its strange, heavy duty, bulky, robust and overpowered, therefore to a "normal" person fuel inefficient features, that would not be applicable in the case of "conventional" family saloon cars, but are often essential when working in harsh, dirty environments, not to mention the conditions of the support lines of a battlefield. Before showing specific examples of the Hummer design, let us briefly attempt to define what we mean by design for service in dirty environments.

It is obvious that the serviceability of machines, or products has a major influence on customer satisfaction, in particular when such machines work or products are being used in critical conditions, in hazardous, dirty environments. If customers are not satisfied, even if they are servicemen, or firefighters, or transport workers in dirty environments who are more or less stuck with the equipment they were given, they will be discarded before the justifiable end of their useful life, creating unnecessary expense, and ultimate failure of the machine, or product.

Product analysis tools that include not just the conventional design for manufacturing, assembly, quality, and total lifecycle but also design for service, and maintenance even in harsh environments (such as fixing the starter motor of the Hummer in a muddy, or dusty, or sandy environment) are capable of comparing the serviceability of alternative design configurations by means of new, powerful virtual reality, as well as more conventional concurrent engineering modeling and simulation tools.

The fundamental methodology that such software tools use, is that they take each element, sub-assembly and assembly of the BOM, or Bill of Material file of the product (or machine) and analyse each of these separately as well as in combination (following the functional relationship diagram, that explains how "things suppose to fit together"). The output comes in the form of estimates of service times and costs, and in the case of the more powerful systems, suggestions for assembly/disassembly operation sequences, generated automatically. Mathematically two important calculations are performed here; one of them is the service efficiency index, the other one is the importance ranking of the service tasks and their repairs.

Plate 1 The "Hummer" or "Humwee"

Plate 2 The "Hummer" or "Humwee"

Briefly, the service efficiency index is trying to advise designers to design with minimum disassembled parts in mind, by justifying, or penalizing the removal of each element, or sub-assembly, or assembly of the BOM file, following the above mentioned functional assembly relationship diagram. Basically, this means computing (under different dirty, or hazardous conditions, represented by "noise" in the control system) the time-based efficiency variable (×_time), defined as

where t_min is the minimum time it takes to carry out a well defined service operation, N_m is the theoretical minimum number of elements, or sub-assemblies, or assemblies (depending on which part of the functional relationship diagram we are working on) that can be justified, and T_s is the estimated time it should take to perform the selected (and justifiable) service task. It should be noted, that in most cases one has to deal with several service efficiency indexes in combination, since there are several parts that need to be serviced to get to the root of a problem.

The importance ranking of the service tasks is a process that attempts to rank factors for each element, sub-assembly and assembly, that should be considered at the design stage, based on the probability of their failures as individual "systems" as well as "combined systems" (i.e. considering that they act as a "member" of the functional relationship model, or diagram). It should be noted, that methods such as failure mode and effect analysis (FMEA), could be excellent complementary tools for this purpose.

Referring to our example (see photos), consider the analysis and reasoning processes designers had to go through when they have decided on the way the bonnet is secured as well as opened (tilting to the front) of the Humwee. Imagine this all-wheel drive, off-road vehicle in a muddy terrain when the driver has to be able to access the engine compartment and service a part under difficult conditions. This justifies the robust, modular design giving all round access and plenty of clearance, as well as the bulky, heavy duty, and in "saloon terminology" ugly, but very practical bonnet locking and quick-release, security latch.

As a summary, the point we make, is that one should be prepared to "think different", by placing the machine, or product into its true working condition, even if it is occasionally dirty and hazardous, already at the design stage, to satisfy serviceability needs in the field.