(3/3) How to Test if Your Organisation is Ready for Distributed Manufacturing?

A step-wise guide to design experiments to explore the feasibility of aligning a distributed manufacturing system with procurement processes in organisations.

Based on insights derived from BRAC’s experience in exploring the scope, challenges, and opportunities in mainstreaming distributed manufacturing in South Asia

*Written by Chathuri Weerasinghe, Social Innovation Lab, BRAC*

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As a part of BRAC’s work with the Frontier Technology Livestreaming (FTL) to test the potential for data aggregation and distributed manufacturing in Bangladesh, we designed an experiment to better understand the feasibility of integrating a distributed manufacturing system as a procurement pathway into a robust institute like BRAC. Upon analysing our overall experience throughout the experiment, we designed a step-wise guide to designing experiments around distributed manufacturing, intending to share our work with a wider community, as well as to create more knowledge materials that can encourage more such initiatives in different contexts.

How to Design a Distributed Manufacturing Experiment?

We divided our experiment into three main phases: Plan, Prepare, and Launch. This blog will elaborate on the last phase of a distributed manufacturing experiment, the ‘Launch’ phase, which can be completed in 6 steps out of the 14 steps framework.

Phase 3: Launch

From BRAC’s experience, this turned out to be the least challenging phase of the experiment!

The 7 steps of the launch for the distributed manufacturing experiment can be considered as follows:

Step 9: Demand generation

The first step in the experiment was gathering the aggregated demand for the finalised products portfolio. BRAC utilised Kobo Toolbox to design a demand generation form, which was deployed among the BRAC HCMP sectors to collect the demand for the finalised products. The aggregate demand was then approved by each HCMP sector lead and the project manager.

Step 10: Demand distribution

Once the demand is assessed and approved by the relevant parties of the user-base, it can be considered distribution ready!

In the BRAC experiment, the approved demand was distributed among the principal and secondary manufacturers based on their daily production capacity, availability of manpower, and area of expertise (See system architecture).

Step 11: Production and quality control

When more than one manufacturer produces the same product that is to be delivered to the same user, ensuring the uniformity of the product quality becomes vital. BRAC utilised the support of a Manufacturing Engineer for this purpose, who was responsible for overlooking the quality control of the production process. The manufacturers were first expected to produce a sample of the products based on the design provided to them (open-source). Once the samples passed through the QC protocols conducted by the Manufacturing Engineer, the full production of the distributed demand quotas began taking place. First Article Inspections (FAI) were conducted by both the manufacturers (self), and the Manufacturing Engineer (institutional).

Step 12: Product distribution

Arranging the distribution of the products manufactured in the experiment depends on the operational formalities of the organisation (I.e., Transportation and logistics protocols, warehouse protocols, etc.). BRAC incorporated its transportation and logistics department to arrange the delivery of the products to the users. All the product pick-up and drop-off locations, and their contact details were shared with the person in charge of product distribution from the transportation department.

Step 13: User feedback

Do not forget to collect user feedback on the quality of the products and the overall delivery system! If you are interested, it is also worthwhile to collect feedback and experience from the manufacturers that were a part of the tested distributed manufacturing network. This feedback can come in handy when you conduct the experiment review- the concluding step of this overall experiment design!

Step 14: Experiment review

It is important to conduct a comprehensive assessment of the experiment once completed. For BRAC, we conducted the evaluation around the scope for progress in the proposed distributed manufacturing system, the feasibility of aligning it with BRAC’s current procurement system, and the challenges we experienced throughout the experiment.

Scope for progress can be identified by assessing the points in the tested distributed manufacturing system that can be digitised or automated, and in which manner. Whereas, the feasibility of aligning a distributed manufacturing system with BRAC’s current procurement process was analysed based on a Systems Evaluation Framework, as well as by addressing the following questions:

• What was the stakeholder responsiveness or willingness to adopt a new supply chain process/ change?
• Did the proposed distributed manufacturing system align with the organisation’s mission?
• What was the operational fit of the system to the institution’s current supply chain?
• What was the feasibility around the cost aspect?
• What was the cost-benefit like?
• Did the experiment demonstrate legal and regulatory feasibility for the distributed manufacturing system to be integrated into your organisation?
• Did the experiment demonstrate feasibility for the distributed manufacturing system to be integrated into your organisation in terms of manufacturers’ production capacity?
• Did the experiment demonstrate adequate quality assurance possibility along the proposed distributed manufacturing process?
• What was the timeliness of the delivery of outcomes like?
• Does the proposed distributed manufacturing system show scope for automation?
• Does the proposed distributed manufacturing system show scope for digitisation?

Challenges in Standardising Distributed Manufacturing at BRAC

We believe that it is important to discuss with our readers the potential challenges of implementing a distributed manufacturing system within institutional contexts as well. During our experiment, we not only observed the feasibility of aligning our proposed distributed manufacturing system with BRAC procurement, but also took notes on the potential challenges the system can undergo along the process of becoming a standardised model within the BRAC aid supply system:

• The concept is relatively recent and limited contextually specific knowledge exists on how a distributed manufacturing system can be incorporated into the supply chains in the development/humanitarian sectors in a country like Bangladesh. This can cause the system to take a longer time in becoming a mainstream model, considering the robustness of the institution.
• The absence of evidence-generating assessments and reviews that compare a conventional procurement system against a distributed manufacturing system can also lead to making the standardisation process a relatively slow one. While this experiment explores the potential areas of BRAC aid supply system (with a particular focus on its procurement aspect) that can benefit from improvements and innovations, no formally and rigorously conducted assessments currently exist as such, which otherwise would have created strong ground evidence to rely on while testing the feasibility and effectiveness of a distributed manufacturing system.
• Getting the proposed distributed manufacturing process approved as a formal procurement process from donor levels can also play a factor in extending the standardisation timeline. As BRAC programmes implement many donor-funded projects which require operations, including procurement approaches, to be approved by the relevant decision-making stakeholders, recognising distributed manufacturing as a standardised procurement process will not only depend on internal approvals, but on external terms (i.e., Donors) as well. Internally, this may be seen as an added responsibility that is time, cost, and resource-intensive.
• It can be challenging to stimulate internal behavioural changes in perceiving distributed manufacturing as a ‘needed’ model rather than a ‘good-to-have’ one, especially given donor-oriented status quos within the institution.

Next Steps

See below the assumptions we generated based on our experiment findings, which will guide us in planning our upcoming experiments.

Following the experiences and learnings gathered during the experiment, BRAC will next focus on digitising the proposed system architecture we have built for the distributed manufacturing system. While it may not be possible to build a fully digitised platform at this point, the experiment helped us understand which components of the distributed manufacturing system are required to be automated and digitised under the existing circumstances (I.e., Quality control, Order placement, Order tracking, Production contracts, Request for Quotation)

As mentioned in our second blog, the production price variations among the manufacturers play an important role in a distributed manufacturing system. Since we kept a rather uniform pricing portfolio for all the included vendors in this experiment, our next aim is to explore how, or whether, vendor prices can create competition among the manufacturers in a distributed manufacturing system, which will, in turn, create an enabling environment for more innovations, and higher quality products.

We also aim to conduct a thorough supply chain analysis of the current BRAC aid system, which will be utilised to conduct a comparative analysis of the current supply chain against one with a distributed manufacturing system incorporated. We believe that an in-depth comparative analysis as such will help us better understand aspects of the proposed distributed manufacturing system, such as cost-effectiveness, sustainable sourcing, vendor competitiveness, scope for innovation within the product portfolio, and room for establishing niche markets.

We would like to hear from you!

While we plan for the next steps, it would also be interesting to hear from our readers about what other aspects of our distributed manufacturing system they think can be tested in our upcoming experiments. Leave your comments below!

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