Advanced Structures India Pvt Ltd is an independent automotive product development company based out of Bangalore, India with operations in India, China and US. Below is blog entry from our engineers about how data and technology assets can be leveraged to delivery exceptional outcomes in value engineering activities . We can be contacted on firstname.lastname@example.org for business enquiries & email@example.com for open positions.
At ASI we believe in persistence that leads to walk an extra mile to find the best solutions for our customers with minimum resources & available information in limited time. The best of our efforts can be explained through 2 of our recent success stories with our most recent & valuable clients.
As numbers speak for themselves, refer the flow chart below that showcase the outstanding results posted for the two clients and how we offered our smart services to them.
The value of a product is defined as the ratio of function to cost. Improving function or reducing cost keeping the other factor constant, increases the overall value of the product. There are 3 key stages of value enhancement process explained below:
Stage 1: Client Support
Right information is the key to value engineering, we aim to seek information from the key business verticals (Engineering, Costing, Supply Chain & Marketing) of our client.
Engineering team connects us with the product or the services that the client offers to its customers. The communication is through 3D- CAD data, 2D drawings, reports, standards & concept/Idea sheets (including the rejected ones).
Costing department provides information on all direct & indirect expenses that goes into the making of the product or offering the services. This cost data is aligned with the part specifications such as manufacturing process, material, size etc. The cost database is used in the cost model to analyse the product specific spends & scope of improvements.
The supply chain connects us with the supplier base and related information. Based on our past experiences with a few customers, it is observed that, supply chain if not managed well can account for maximum scope of optimization. Also, it has been found that the client misses out on the optimization part due to project deadline constraints.
For instance, with one of our clients we could reduce the cost of overall product by 5% only by focusing on packaging efficiency & transportation. (Refer the snapshot below for details)
In order to understand the usability of all the features and attributes of a product or a service by the customers, representative from marketing department helps us connect with the consumers of product or the services offered by the client. The key data is obtained by doing surveys & clinics with a sample set of 15-20 customers. This activity suggests what to add or subtract from the product or the services.
In one instance, we have found that the client offered features in the product for some specific purpose that was used only by 20% of the total customer base. However, the cost of adding that particular feature to the product cost a huge sum that was not justified. We helped the client work on developing a variant of that product which incurred only the variable cost. This resulted in increased profit margin on 80 % of products sold without that feature to its customers.
Stage 2: Data Handling
In order to garner information/data in an effective manner, ASI’s software team develops smart tools that can collect maximum information in short time. These tools are flexible and custom made as per project requirements.
For instance, we digitized more than 35000 drawings (in the form of CAD or PDF’s) to fetch 45 key specifications per part in just 40 days for one customer. For another customer as a part of value engineering, we scanned through more than 3000 parts and derived specifications w.r.t operator ergonomics, assembly locus & design philosophy.
Data Scrubbing & Shortlisting
Information is useful only when it is correct, so the first thing after receiving data is to chop off the irrelevant or incorrect information.
We believe in 80-20 principle and to find out the most impacting 20% parts, parametric equations called ‘Logic Filters’ are devised. The parameters for these logic filters are selected from 30-40 key specifications like manufacturing method, material, coating/plating & weight etc. derived from the information obtained in stage 1.
Eventually, these equations result in narrowing down the information to improve focus and possibility of maximum savings through Value Engineering. For instance, the below 2 examples showcase the subtle way of data shortlisting.
The graph A shows the variation in the ratio (Product Cost/Kg of RM) for a set of 80 parts made from same material.
The graph B shows the variation in the ratio (Surface Coating/Unit Area) for a set of 80 parts with similar plating specifications.
The parts which are not following the trend (a small percentage) can be identified from the above 2 graphs & shortlisted for next stage i.e. Value Engineering & Value Analysis.
Similarly, all relevant parameters for the obtained data during stage 1 can be studied and logical equations can be formed to identify and select the outliers/odd ones.
Stage 3: Value Engineering
Value Drivers Identification
The data collected from marketing is utilized in ascertaining the attributes and features in the product that is in demand at maximum & minimum. The maximum demanded attributes should be projected more towards the customer and the minimum or the unused features should be removed/reduced. The values for which the customer is willing to pay is the critical ones and everything else is irrelevant.
For instance, the table below represents the product features of a kit with its respective value rating. Final rating values are mean of survey data collected from 50 users (Top Management). As we can see, the users gave much preference to AIS compliance, Fuel economy, Serviceability and durability. Other features like weight, accessibility and cost are considered secondary. The survey also revealed that the users are least concerned about aesthetics. This helped in reducing the heavy unnecessary cost that went into painting the kit for aesthetics.
Sample Size: 50 Users (Top Management)
By teardown we mean analysis in detail, be it a process, technique, product or the ideas. Generally, teardown is necessary to understand the offerings of other competitors that are selling their products with what features, what quality and at what cost. But, that’s not where the activity ends, we have to see beyond what is obvious and visible that includes capturing the design philosophy of the competitor.
For an OEM, we benchmarked its product with several competitor products. All the competitor products were torn down to last level and other than a few obvious observations, it was found that one of the OEM’s had a modular design philosophy. That particular OEM had various products from different segments which utilized the same set of modules to manufacture them.
We suggested a similar methodology to our client which resulted in success with numbers as shown below.
We have a well-setup lab with bays that can disassemble multiple vehicles in parallel without compromising information security.
At our Tear Down lab, we offer:
- Disassembling products up-to its last level.
- BOM creation with easy part numbering and assembly level identification
- Features Mapping (Assembly & Part Level)
- Assembly locus/sequence study
- Key Specifications mapping (Material, Weight, Size, Coating etc.)
- Tools utilization (Type, quantity, usability etc.)
- Part/Tool/Feature commonisation study.
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Outcomes, Feasibility Study & Implementation
Once all the data is analysed and proposed methods or ideas are compiled, we run the feasibility study within the relevant departments of the client. Later an implementation plan is orchestrated considering the priority that is decided based on the business requirements of the client.
Pratik Kumar Shukla